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R: Linearized Bregman solver for composite conditionally...

potts

R Documentation

Linearized Bregman solver for composite conditionally likelihood of Potts model with lasso penalty and block-group penalty.

Description

Solver for the entire solution path of coefficients.

Usage

potts(X, kappa, alpha, c = 1, tlist, nt = 100, trate = 100,
  group = FALSE, intercept = TRUE, print = FALSE)

Arguments

`X`	An n-by-p matrix of variables.
`kappa`	The damping factor of the Linearized Bregman Algorithm that is defined in the reference paper. See details.
`alpha`	Parameter in Linearized Bregman algorithm which controls the step-length of the discretized solver for the Bregman Inverse Scale Space. See details.
`c`	Normalized step-length. If alpha is missing, alpha is automatically generated by `alpha=cn/(kappa\|\|XX^T*XX\|\|_2)`, where XX is 0-1 indicator matrix induced by the class of each Xi. Default is 1. It should be in (0,2). If beyond this range the path may be oscillated at large t values.
`tlist`	Parameters t along the path.
`nt`	Number of t. Used only if tlist is missing. Default is 100.
`trate`	tmax/tmin. Used only if tlist is missing. Default is 100.
`group`	Whether to use a block-wise group penalty, Default is FALSE
`intercept`	if TRUE, an intercept is included in the model (and not penalized), otherwise no intercept is included. Default is TRUE.
`print`	If TRUE, the percentage of finished computation is printed.

Details

The data matrix X is transformed into a 0-1 indicator matrix D with each column D_{jk} means 1(X_j)==k. The Potts model here used is described as following:

P(x) sim exp(∑_{jk} a_{0,jk}1(x_i=1) + d^T Θ d/2)

where Θ is p-by-p symmetric and 0 on diagnal. Then conditional on x_{-j}

P(x_j=k) sim exp(∑_{k} a_{0,jk} + ∑_{i\neq j,r}θ_{jk,ir}d_{ir})

then the composite conditional likelihood is like this:

- ∑_{j} condloglik(X_j | X_{-j})

Value

A "potts" class object is returned. The list contains the call, the path, the intercept term a0 and value for alpha, kappa, t.

Author(s)

Jiechao Xiong

Examples


X = matrix(floor(runif(200*10)*3),200,10)
obj = potts(X,10,nt=100,trate=10,group=TRUE)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(Libra)
Loading required package: nnls
Loaded Libra 1.5

> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/Libra/potts.Rd_%03d_medium.png", width=480, height=480)
> ### Name: potts
> ### Title: Linearized Bregman solver for composite conditionally likelihood
> ###   of Potts model with lasso penalty and block-group penalty.
> ### Aliases: potts
> ### Keywords: regression
> 
> ### ** Examples
> 
> 
> X = matrix(floor(runif(200*10)*3),200,10)
> obj = potts(X,10,nt=100,trate=10,group=TRUE)
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>