# f3st: Stepwise selection of covariates In gausscov: The Gaussian Covariate Method for Variable Selection

 f3st R Documentation

## Stepwise selection of covariates

### Description

Stepwise selection of covariates

### Usage

```f3st(y,x,m,kexmx=100,p0=0.01,nu=1,kmn=0,kmx=0,mx=21,lm=1000,kex=0,sub=T,inr=T,xinr=F,qq=0)
```

### Arguments

 `y` Dependent variable `x` Covariates `m` The number of iterations `kexmx` The maximum number of covariates in an approximation `p0` The P-value cut-off `nu` The order statistic of Gaussian covariates used for comparison `kmn` The minimum number of included covariates irrespective of cut-off P-value `kmx` The maximum number of included covariates irrespective of cut-off P-value. `mx` The maximum number covariates for an all subset search `lm` The maximum number of approximations. `kex` The excluded covariates `sub` Logical if TRUE best subset selected `inr` Logical if TRUE include intercept if not present `xinr` Logical if TRUE intercept already present `qq` The number of covariates to choose from. If qq=0 the number of covariates of x is used.

### Value

covch The sum of squared residuals and the selected covariates ordered in increasing size of sum of squared residuals.

lai The number of rows of covch

### Examples

```data(leukemia)
a<-f3st(leukemia[],leukemia[],m=2,kexmx=5,kmn=5,sub=TRUE)
```

gausscov documentation built on April 26, 2022, 5:07 p.m.