Package: spca 1.1.1

Installation | Usage | Example | Load data | Preliminary PCA | Compute the sparse loadings | Inspect spca results | Variable groups | Comparison of two or more spca solutions

title: "Computing Least Squares Sparse Principal Components with the spca Package"author: "Giovanni Maria Merola"date: "r Sys.Date()"output: rmarkdown::html_vignettevignette: >%\VignetteIndexEntry{Computing Least Squares Sparse Principal Components with spca}%\VignetteEngine{knitr::rmarkdown}%\VignetteEncoding{UTF-8}%\VignetteDepends{spca}knit: (function(input, ...) rmarkdown::render(input, output_dir = dirname(normalizePath(input)), ...)) | Introduction | LS-SPCA in brief | The spca package | Application | pca() | spca() | print() | summary() | plot() | Fixed indices | Compare solutions | Variable groups | Create an spca object | Comparison of LS-SPCA variants | Computation methods | Variable selection methods | alpha | Comparison with conventional SPCA | Tall matrices | Fat matrices | References