README.md

In ohishim/GFLlogit: Coordinate descent algorithm of generalized fused Lasso logistic regression for multivariate trend filtering

GFLlogit (v1.0.0)

cite this package: Ohishi, M. (2021). GFLlogit: Coordinate optimization for GFL logistic regression. R package version 1.0.0. https://github.com/ohishim/GFLlogit

Installation

You can install the R package GFLlogit from GitHub with:

# install.packages("devtools")
devtools::install_github("ohishim/GFLlogit")

Example

This package has an example dataset as the two objects exdata and adj. The exdata has 200 individuals for 10 areas and 20 time points. The adj has adjacent information of 200 spatio-temporal points. This package estimates spatio-temporal trends.

The GFLlogit procedure can be executed as follows:

library(GFLlogit)

m <- exdata$m
y <- exdata$y
adjCD <- split(adj$adj, adj$lab)

res <- GFLlogit(m, y, adjCD)

The output res takes a form of a list object. For example, you can obtain GFL estimates by res$mu.hat.

Reference

1. Ohishi, M., Yamamura, M. & Yanagihara, H. (2022). Coordinate descent algorithm of generalized fused Lasso logistic regression for multivariate trend filtering. Jpn. J. Stat. Data Sci., 5, 535-551. doi: 10.1007/s42081-022-00162-2

ohishim/GFLlogit documentation built on Feb. 6, 2023, 9 p.m.