mht (version 3.1.2)

refit.mht.order: Refit a mht.order object

Description

Refit a mht.order object for a new observation Ynew and/or a new order ordrenew

Usage

"refit"(object,Ynew,ordrenew,IT,var_nonselect,sigma,showresult,...)

Arguments

object

Object of class "mht.order" as obtained from mht.

Ynew

Response variable of length n.

ordrenew

Vector from which the varibles are to be ordered, it can be a partial order. If absent, data is considers to be already ordered; Default is (1,2,..,p).

IT

Number of simulations in the calculation of the quantile. Default is 10000.

var_nonselect

Number of variables that don't undergo feature selection. They have to be in the first columns of data. Default is 1, the selection is not performed on the intercept.

sigma

Value of the variance if it is known; 0 otherwise. Default is 0.

showresult

Logical value. if TRUE, show the value of the statistics and the estimated quantile at each step of the procedure. Default is TRUE.

...

not used.

Value

data

A list containing:

• Y - the input response vector
• means.X - Vector of means of the input data matrix.
• sigma.X - Vector of variances of the input data matrix.

coefficients

Matrix of the estimated coefficients. Each row concerns a specific user level alpha.

residuals

Matrix of the residuals. Each row concerns a specific user level alpha.

relevant_var

Set of the relevant variables. Each row concerns a specific user level alpha

fitted.values

Matrix of the fitted values, each column concerns a specific user level alpha.

kchap

Vector containing the length of the estimated set of relevant variables, for each values of alpha.

quantile

The estimated type I error to be used in the second step of the procedure in order to have a test of level alpha, each column stands for one test. See F.Rohart (2011) for details.

call

The call that has been used.

call.old

The call that produced the initial 'object'.

Details

see mht.order for details.

Examples

## Not run: 
# x=matrix(rnorm(100*20),100,20)
# beta=c(rep(2,5),rep(0,15))
# y=x%*%beta+rnorm(100)
# ynew=x%*%beta+rnorm(100)
# 
# # mht.order
# mod.order=mht.order(x,y)
# 
# # refit mht.order on a new vector of observation
# mod.refit=refit(mod.order,ynew)
# ## End(Not run)