Science Score: 26.0%

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Keywords

r statistical-learning tensor
Last synced: 6 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: yuting1214
  • Language: R
  • Default Branch: main
  • Homepage:
  • Size: 3.14 MB
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Topics
r statistical-learning tensor
Created about 4 years ago · Last pushed over 1 year ago
Metadata Files
Readme

README.md

CRAN_Status_Badge Downloads Total Downloads

TensorTest2D

An implementation of fitting generalized linear models on second-order tensor type data. The functions within this package mainly focus on parameter estimation, including parameter coefficients and standard deviation.

Installation

git clone https://github.com/yuting1214/TensorTest2D R CMD INSTALL TensorTest2D or in R console window type the following install.packages("TensorTest2D")

Quick start

``` library(TensorTest2D)

Simulate data

n <- 500 # number of observations nP <- 3; nG <- 64 # dimension of 3-D tensor variables. nd <- 1 # number of numerical variable, if nd == 1, numerical variable equals to intercept. betaTrue <- rep(1, nd) BTrue <- c(1,1,1)%*%t(rnorm(nG)) + c(0, .5, .5)%%t(rnorm(nG)) BTrue <- B_True / 10 W <- matrix(rnorm(nnd), n, nd); W[,1] <- 1 X <- array(rnorm(nn_PnG), dim=c(nP, n_G, n))

Regression Data

yR<- as.vector(W%*%betaTrue + X%hp%BTrue + rnorm(n)) DATAR <- list(y = y_R, X = X, W = W)

Execution (Regression)

resultR <- tensorReg2D(y = DATAR$y, X = DATAR$X, W=NULL, nR = 1, family = "gaussian", opt = 1, max_ite = 100, tol = 10^(-7) )

Visualization

image(BTrue);image(resultR$BEST) head(predict(resultR, DATA_R$X)) ```

Relevant Packages

  • tensor: The tensor product of two arrays is notionally an outer product of the arrays collapsed in specific extents by summing along the appropriate diagonals.
  • rTensor: Tools for Tensor Analysis and Decomposition
  • tensorregress: Implement the alternating algorithm for supervised tensor decomposition with interactive side information.

Publications

  • Ping-Yang Chen/Hsing-Ming Chang/Yu-Ting Chen/Jung-Ying Tzeng/Sheng-Mao Chang* (2022) ,TensorTest2D: Fitting Generalized Linear Models with Matrix Covariates,The R Journal,14,152-163,SSCI

Owner

  • Login: yuting1214
  • Kind: user

R, Python user. Interested in statistical computing, statistical simulation

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Last synced: 8 months ago

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  • Commits: 3
  • Committers: 1
  • Avg Commits per committer: 3.0
  • Development Distribution Score (DDS): 0.0
Top Committers
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Mark Chen 3****4 11

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Packages

  • Total packages: 1
  • Total downloads:
    • cran 264 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 7
  • Total maintainers: 1
cran.r-project.org: TensorTest2D

Fitting Second-Order Tensor Data

  • Versions: 7
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 264 Last month
Rankings
Forks count: 28.8%
Dependent packages count: 29.8%
Stargazers count: 35.2%
Dependent repos count: 35.5%
Average: 38.9%
Downloads: 65.0%
Maintainers (1)
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.5.0 depends
  • grDevices * imports
  • graphics * imports
  • stats * imports
  • utils * imports
  • abind * suggests
  • glmnet * suggests
  • knitr * suggests
  • rmarkdown * suggests
  • testthat * suggests