- using R Under development (unstable) (2024-12-17 r87446 ucrt)
- using platform: x86_64-w64-mingw32
- R was compiled by
gcc.exe (GCC) 13.3.0
GNU Fortran (GCC) 13.3.0
- running under: Windows Server 2022 x64 (build 20348)
- using session charset: UTF-8
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- this is package 'tensorregress' version '5.1'
- package encoding: UTF-8
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See the install log for details.
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41 | \code{tsr} {a list of simulated tensors, with the number of replicates specified by \code{dup}}
| ^
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43 | \code{X_covar1} {a matrix, side information on first mode}
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45 | \code{X_covar2} {a matrix, side information on second mode}
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47 | \code{X_covar3} {a matrix, side information on third mode}
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49 | \code{W} {a list of orthogonal factor matrices - one for each mode, with the number of columns given by \code{core_shape}}
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51 | \code{G} {an array, core tensor with size specified by \code{core_shape}}
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53 | \code{C_ts} {an array, coefficient tensor, Tucker product of \code{G},\code{A},\code{B},\code{C}}
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55 | \code{U} {an array, linear predictor,i.e. Tucker product of \code{C_ts},\code{X_covar1},\code{X_covar2},\code{X_covar3}}
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53 | \code{W} {a list of orthogonal factor matrices - one for each mode, with the number of columns given by \code{core_shape}}
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55 | \code{G} {an array, core tensor with the size specified by \code{core_shape}}
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57 | \code{C_ts} {an array, coefficient tensor, Tucker product of \code{G},\code{A},\code{B},\code{C}}
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59 | \code{U} {linear predictor,i.e. Tucker product of \code{C_ts},\code{X_covar1},\code{X_covar2},\code{X_covar3}}
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61 | \code{lglk} {a vector containing loglikelihood at convergence}
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63 | \code{sigma} {a scalar, estimated error variance (for Gaussian tensor) or dispersion parameter (for Bernoulli and Poisson tensors)}
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65 | \code{violate} {a vector listing whether each iteration violates the max norm constraint on the linear predictor, \code{1} indicates violation}
| ^
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- DONE
Status: 1 NOTE