Learn R Programming

SFM (version 0.2.1)

A Package for Analyzing Skew Factor Models

Description

Generates Skew Factor Models data and applies Sparse Online Principal Component (SOPC), Incremental Principal Component (IPC), Projected Principal Component (PPC), Perturbation Principal Component (PPC), Stochastic Approximation Principal Component (SAPC), Sparse Principal Component (SPC) and other PC methods to estimate model parameters. It includes capabilities for calculating mean squared error, relative error, and sparsity of the loading matrix.The philosophy of the package is described in Guo G. (2023) .

Copy Link

Version

Install

install.packages('SFM')

Monthly Downloads

149

Version

0.2.1

License

MIT + file LICENSE

Maintainer

Guangbao Guo

Last Published

April 15th, 2025

Functions in SFM (0.2.1)

protein

Data Frame 'protein'
calculate_errors

calculate_errors Function
yacht_hydrodynamics

Data Frame 'yacht_hydrodynamics'
concrete_slump

Data Frame 'concrete_slump'
SPC.SFM

Apply the SPC method to the Skew factor model
FanPC.SFM

Apply the FanPC method to the Skew factor model
PPC2.SFM

Apply the PPC method to the Skew factor model
PC2.SFM

Apply the PC method to the Laplace factor model
IPC.SFM

Apply the IPC method to the Skew factor model
PPC1.SFM

Apply the PPC method to the Skew factor model
OPC.SFM

Apply the OPC method to the Skew factor model
GulPC.SFM

Apply the GulPC method to the Skew factor model
PC1.SFM

Apply the PC method to the Laplace factor model
SFM

The SFM function is to generate Skew Factor Models data.
SAPC.SFM

Stochastic Approximation Principal Component Analysis
SOPC.SFM

SOPC Estimation Function