* using log directory ‘/home/hornik/tmp/R.check/r-devel-gcc/Work/PKGS/Renvlp.Rcheck’
* using R Under development (unstable) (2025-02-25 r87824)
* using platform: x86_64-pc-linux-gnu
* R was compiled by
    gcc-14 (Debian 14.2.0-16) 14.2.0
    GNU Fortran (Debian 14.2.0-16) 14.2.0
* running under: Debian GNU/Linux trixie/sid
* using session charset: UTF-8
* checking for file ‘Renvlp/DESCRIPTION’ ... OK
* checking extension type ... Package
* this is package ‘Renvlp’ version ‘3.4.5’
* checking package namespace information ... OK
* checking package dependencies ... OK
* checking if this is a source package ... OK
* checking if there is a namespace ... OK
* checking for executable files ... OK
* checking for hidden files and directories ... OK
* checking for portable file names ... OK
* checking for sufficient/correct file permissions ... OK
* checking whether package ‘Renvlp’ can be installed ... OK
See 'https://www.r-project.org/nosvn/R.check/r-devel-linux-x86_64-debian-gcc/Renvlp-00install.html' for details.
* checking package directory ... OK
* checking for future file timestamps ... OK
* checking DESCRIPTION meta-information ... OK
* checking top-level files ... OK
* checking for left-over files ... OK
* checking index information ... OK
* checking package subdirectories ... OK
* checking code files for non-ASCII characters ... OK
* checking R files for syntax errors ... OK
* checking whether the package can be loaded ... [0s/0s] OK
* checking whether the package can be loaded with stated dependencies ... [0s/0s] OK
* checking whether the package can be unloaded cleanly ... [0s/0s] OK
* checking whether the namespace can be loaded with stated dependencies ... [0s/0s] OK
* checking whether the namespace can be unloaded cleanly ... [0s/0s] OK
* checking loading without being on the library search path ... [0s/0s] OK
* checking use of S3 registration ... OK
* checking dependencies in R code ... OK
* checking S3 generic/method consistency ... OK
* checking replacement functions ... OK
* checking foreign function calls ... OK
* checking R code for possible problems ... [26s/32s] OK
* checking Rd files ... [1s/1s] NOTE
checkRd: (-1) testcoef.env.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                ^
checkRd: (-1) testcoef.env.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                        ^
checkRd: (-1) testcoef.env.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                               ^
checkRd: (-1) testcoef.env.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                ^
checkRd: (-1) testcoef.env.apweights.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model with nonconstant errors.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                        ^
checkRd: (-1) testcoef.env.apweights.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model with nonconstant errors.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                ^
checkRd: (-1) testcoef.env.apweights.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model with nonconstant errors.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                       ^
checkRd: (-1) testcoef.env.apweights.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model with nonconstant errors.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                                        ^
checkRd: (-1) testcoef.env.tcond.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model with t-distributed errors.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                          ^
checkRd: (-1) testcoef.env.tcond.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model with t-distributed errors.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                  ^
checkRd: (-1) testcoef.env.tcond.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model with t-distributed errors.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                         ^
checkRd: (-1) testcoef.env.tcond.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model with t-distributed errors.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                                          ^
checkRd: (-1) testcoef.genv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta[[i]] R = A, versus Ha: L beta[[i]] R != A.  The beta is estimated by the groupwise envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta[[i]] = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                         ^
checkRd: (-1) testcoef.genv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta[[i]] R = A, versus Ha: L beta[[i]] R != A.  The beta is estimated by the groupwise envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta[[i]] = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                 ^
checkRd: (-1) testcoef.genv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta[[i]] R = A, versus Ha: L beta[[i]] R != A.  The beta is estimated by the groupwise envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta[[i]] = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                        ^
checkRd: (-1) testcoef.genv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta[[i]] R = A, versus Ha: L beta[[i]] R != A.  The beta is estimated by the groupwise envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta[[i]] = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                                         ^
checkRd: (-1) testcoef.henv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the heteroscedastic envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                ^
checkRd: (-1) testcoef.henv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the heteroscedastic envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                        ^
checkRd: (-1) testcoef.henv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the heteroscedastic envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                               ^
checkRd: (-1) testcoef.henv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the heteroscedastic envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                                ^
checkRd: (-1) testcoef.logit.env.Rd:18: Lost braces
    18 | This function tests for hypothesis H0: L beta = A, versus Ha: L beta != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta - A) hat{Sigma}^{-1} vec(L beta - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta - A). The reference distribution is chi-squared distribution with degrees of freedom d1. 
       |                                                                                                                                                                                                                                                                                     ^
checkRd: (-1) testcoef.logit.env.Rd:18: Lost braces; missing escapes or markup?
    18 | This function tests for hypothesis H0: L beta = A, versus Ha: L beta != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta - A) hat{Sigma}^{-1} vec(L beta - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta - A). The reference distribution is chi-squared distribution with degrees of freedom d1. 
       |                                                                                                                                                                                                                                                                                             ^
checkRd: (-1) testcoef.logit.env.Rd:18: Lost braces; missing escapes or markup?
    18 | This function tests for hypothesis H0: L beta = A, versus Ha: L beta != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta - A) hat{Sigma}^{-1} vec(L beta - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta - A). The reference distribution is chi-squared distribution with degrees of freedom d1. 
       |                                                                                                                                                                                                                                                                                                                  ^
checkRd: (-1) testcoef.logit.env.Rd:18: Lost braces
    18 | This function tests for hypothesis H0: L beta = A, versus Ha: L beta != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta - A) hat{Sigma}^{-1} vec(L beta - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta - A). The reference distribution is chi-squared distribution with degrees of freedom d1. 
       |                                                                                                                                                                                                                                                                                                                                                                   ^
checkRd: (-1) testcoef.penv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta1 R = A, versus Ha: L beta1 R != A.  The beta is estimated by the partial envelope model.  If L = Ir, R = Ip1 and A = 0, then the test is equivalent to the standard F test on if beta1 = 0.  The test statistics used is vec(L beta1 R - A) hat{Sigma}^{-1} vec(L beta1 R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta1 R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                              ^
checkRd: (-1) testcoef.penv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta1 R = A, versus Ha: L beta1 R != A.  The beta is estimated by the partial envelope model.  If L = Ir, R = Ip1 and A = 0, then the test is equivalent to the standard F test on if beta1 = 0.  The test statistics used is vec(L beta1 R - A) hat{Sigma}^{-1} vec(L beta1 R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta1 R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                      ^
checkRd: (-1) testcoef.penv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta1 R = A, versus Ha: L beta1 R != A.  The beta is estimated by the partial envelope model.  If L = Ir, R = Ip1 and A = 0, then the test is equivalent to the standard F test on if beta1 = 0.  The test statistics used is vec(L beta1 R - A) hat{Sigma}^{-1} vec(L beta1 R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta1 R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                              ^
checkRd: (-1) testcoef.penv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta1 R = A, versus Ha: L beta1 R != A.  The beta is estimated by the partial envelope model.  If L = Ir, R = Ip1 and A = 0, then the test is equivalent to the standard F test on if beta1 = 0.  The test statistics used is vec(L beta1 R - A) hat{Sigma}^{-1} vec(L beta1 R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta1 R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                               ^
checkRd: (-1) testcoef.pois.env.Rd:18: Lost braces
    18 | This function tests for hypothesis H0: L beta = A, versus Ha: L beta != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta - A) hat{Sigma}^{-1} vec(L beta - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta - A). The reference distribution is chi-squared distribution with degrees of freedom d1. 
       |                                                                                                                                                                                                                                                                                     ^
checkRd: (-1) testcoef.pois.env.Rd:18: Lost braces; missing escapes or markup?
    18 | This function tests for hypothesis H0: L beta = A, versus Ha: L beta != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta - A) hat{Sigma}^{-1} vec(L beta - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta - A). The reference distribution is chi-squared distribution with degrees of freedom d1. 
       |                                                                                                                                                                                                                                                                                             ^
checkRd: (-1) testcoef.pois.env.Rd:18: Lost braces; missing escapes or markup?
    18 | This function tests for hypothesis H0: L beta = A, versus Ha: L beta != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta - A) hat{Sigma}^{-1} vec(L beta - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta - A). The reference distribution is chi-squared distribution with degrees of freedom d1. 
       |                                                                                                                                                                                                                                                                                                                  ^
checkRd: (-1) testcoef.pois.env.Rd:18: Lost braces
    18 | This function tests for hypothesis H0: L beta = A, versus Ha: L beta != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta - A) hat{Sigma}^{-1} vec(L beta - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta - A). The reference distribution is chi-squared distribution with degrees of freedom d1. 
       |                                                                                                                                                                                                                                                                                                                                                                   ^
checkRd: (-1) testcoef.rrenv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the reduced rank envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                             ^
checkRd: (-1) testcoef.rrenv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the reduced rank envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                     ^
checkRd: (-1) testcoef.rrenv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the reduced rank envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                            ^
checkRd: (-1) testcoef.rrenv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the reduced rank envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                             ^
checkRd: (-1) testcoef.rrenv.apweights.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the reduced rank envelope model that accommodates nonconstant error variance.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                          ^
checkRd: (-1) testcoef.rrenv.apweights.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the reduced rank envelope model that accommodates nonconstant error variance.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                  ^
checkRd: (-1) testcoef.rrenv.apweights.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the reduced rank envelope model that accommodates nonconstant error variance.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                         ^
checkRd: (-1) testcoef.rrenv.apweights.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the reduced rank envelope model that accommodates nonconstant error variance.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                                                                          ^
checkRd: (-1) testcoef.senv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the scaled envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                       ^
checkRd: (-1) testcoef.senv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the scaled envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                               ^
checkRd: (-1) testcoef.senv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the scaled envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                      ^
checkRd: (-1) testcoef.senv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the scaled envelope model.  If L = Ir, R = Ip and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                       ^
checkRd: (-1) testcoef.stenv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the simultaneous envelope model.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                             ^
checkRd: (-1) testcoef.stenv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the simultaneous envelope model.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                     ^
checkRd: (-1) testcoef.stenv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the simultaneous envelope model.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                            ^
checkRd: (-1) testcoef.stenv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the simultaneous envelope model.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                             ^
checkRd: (-1) testcoef.sxenv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the scaled envelope model in the predictor space.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                              ^
checkRd: (-1) testcoef.sxenv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the scaled envelope model in the predictor space.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                      ^
checkRd: (-1) testcoef.sxenv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the scaled envelope model in the predictor space.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                             ^
checkRd: (-1) testcoef.sxenv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the scaled envelope model in the predictor space.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                                              ^
checkRd: (-1) testcoef.xenv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                   ^
checkRd: (-1) testcoef.xenv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                           ^
checkRd: (-1) testcoef.xenv.Rd:19: Lost braces; missing escapes or markup?
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                  ^
checkRd: (-1) testcoef.xenv.Rd:19: Lost braces
    19 | This function tests for hypothesis H0: L beta R = A, versus Ha: L beta R != A.  The beta is estimated by the envelope model in predictor space.  If L = Ip, R = Ir and A = 0, then the test is equivalent to the standard F test on if beta = 0.  The test statistic used is vec(L beta R - A) hat{Sigma}^{-1} vec(L beta R - A)^{T}, where beta is the envelope estimator and hat{Sigma} is the estimated asymptotic covariance of vec(L beta R - A). The reference distribution is chi-squared distribution with degrees of freedom d1 * d2. 
       |                                                                                                                                                                                                                                                                                                                                                                                   ^
checkRd: (-1) xenv.Rd:28: Lost braces; missing escapes or markup?
    28 | \item{eta}{The estimated eta.  According to the envelope parameterization, beta = Gamma * Omega^{-1} * eta.}
       |                                                                                                 ^
* checking Rd metadata ... OK
* checking Rd line widths ... OK
* checking Rd cross-references ... OK
* checking for missing documentation entries ... OK
* checking for code/documentation mismatches ... OK
* checking Rd \usage sections ... OK
* checking Rd contents ... OK
* checking for unstated dependencies in examples ... OK
* checking contents of ‘data’ directory ... OK
* checking data for non-ASCII characters ... [0s/0s] OK
* checking data for ASCII and uncompressed saves ... OK
* checking examples ... [38s/47s] OK
* checking PDF version of manual ... [7s/9s] OK
* checking HTML version of manual ... [4s/6s] OK
* checking for non-standard things in the check directory ... OK
* DONE
Status: 1 NOTE