# coef.splitSelect: Coefficients for splitSelect object In splitSelect: Best Split Selection Modeling for Low-Dimensional Data

## Description

`coef.splitSelect` returns the coefficients for a splitSelect object.

## Usage

 ```1 2``` ```## S3 method for class 'splitSelect' coef(object, ...) ```

## Arguments

 `object` An object of class splitSelect. `...` Additional arguments for compatibility.

## Value

A matrix with the coefficients of the `splitSelect` object.

## Author(s)

Anthony-Alexander Christidis, anthony.christidis@stat.ubc.ca

## See Also

`splitSelect`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32``` ```# Setting the parameters p <- 4 n <- 30 n.test <- 5000 beta <- rep(5,4) rho <- 0.1 r <- 0.9 SNR <- 3 # Creating the target matrix with "kernel" set to rho target_cor <- function(r, p){ Gamma <- diag(p) for(i in 1:(p-1)){ for(j in (i+1):p){ Gamma[i,j] <- Gamma[j,i] <- r^(abs(i-j)) } } return(Gamma) } # AR Correlation Structure Sigma.r <- target_cor(r, p) Sigma.rho <- target_cor(rho, p) sigma.epsilon <- as.numeric(sqrt((t(beta) %*% Sigma.rho %*% beta)/SNR)) # Simulate some data x.train <- mvnfast::rmvn(30, mu=rep(0,p), sigma=Sigma.r) y.train <- 1 + x.train %*% beta + rnorm(n=n, mean=0, sd=sigma.epsilon) # Generating the coefficients for a fixed partition of the variables split.out <- splitSelect(x.train, y.train, G=2, use.all=TRUE, fix.partition=list(matrix(c(2,2), ncol=2, byrow=TRUE)), fix.split=NULL, intercept=TRUE, group.model="glmnet", alphas=0) coef(split.out) ```

splitSelect documentation built on Nov. 9, 2021, 9:07 a.m.