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LFM (version 0.3.3)

Laplace Factor Model Analysis and Evaluation

Description

Enables the generation of Laplace factor models across diverse Laplace distributions and facilitates the application of Sparse Online Principal Component (SOPC), Incremental Principal Component (IPC), Perturbation Principal Component (PPC), Stochastic Approximation Principal Component (SAPC), Sparse Principal Component (SPC) and other PC methods and Farm Test methods to these models. Evaluates the efficacy of these methods within the context of Laplace factor models by scrutinizing parameter estimation accuracy, mean square error, and the degree of sparsity.

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Version

Install

install.packages('LFM')

Monthly Downloads

189

Version

0.3.3

License

MIT + file LICENSE

Maintainer

Guangbao Guo

Last Published

December 6th, 2025

Functions in LFM (0.3.3)

Riboflavin Production Data (Top 100 Genes)

Protein Secondary Structure Data

Apply the PPC method to the Laplace factor model

Apply the PPC method to the Laplace factor model

Bankruptcy data

Wholesale Customers Data

yacht_hydrodynamics

Yacht Hydrodynamics Data

Apply the SPC method to the Laplace factor model

In Vehicle Coupon Recommendation Data

Riboflavin Production Data

Distributed general unilateral loading principal component

Apply the IPC method to the Laplace factor model

Distributed projection principal component

Apply the PC method to the Laplace factor model

Apply the traditional principal component method to the Laplace factor model

Generate Laplace factor models

Apply the Farmtest method to the Laplace factor model

Apply the GulPC method to the Laplace factor model

Apply the FanPC method to the Laplace factor model

Apply the OPC method to the Laplace factor model

Apply the SOPC method to the Laplace factor model

Apply the SAPC method to the Laplace factor model

Factor Model Testing with Wald, GRS, PY tests and FDR control

Concrete Slump Test Data

ionosphere Data