Package: spca 1.1.5

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

title: "spca Extended Vignette"author: "Giovanni Maria Merola"date: "r Sys.Date()"output: rmarkdown::html_vignettevignette: >%\VignetteIndexEntry{spca extended vignette}%\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 | A typical SPCA workflow using spca | PCA | SPCA | summary() | Comparison of SPCA with PCA | Analysis of the sparse solutions | print() | plot() | Comparison of two LS-SPCA solutions | Fixed indices | Create an spca object | Practical recommendations | Application to larger datasets | MSSCQ data | Isolet data | Colon data | Comparison of LS-SPCA variants | Computation methods | Variable selection methods | alpha | Comparison with conventional SPCA | Tall matrices | Fat matrices | References