extract.object: 'extract.object' fits a multivariate quantile regression and...

View source: R/clustEff.R

extract.objectR Documentation

extract.object fits a multivariate quantile regression and extracts objects for the cluster effects algorithm.

Description

extract.object fits a multivariate quantile regression and extracts objects for the cluster effects algorithm.

Usage

extract.object(Y, X, intercept=TRUE, formula.p=~slp(p, 3), s, object, p, which)

Arguments

Y

A multivariate response matrix of dimension n x q1, or a vector of length n.

X

The covariates matrix of dimension n x q2.

intercept

If TRUE, the intercept is included in the model.

formula.p

a one-sided formula of the form ~ b1(p, ...) + b2(p, ...) + ...

s

An optional 0/1 matrix that allows to exclude some model coefficients (see ‘Examples’).

object

An object of class “iqr”. If missing, Y and X have to be supplied.

p

The percentiles used in quantile regression coefficient modeling. If missing a default sequence is choosen.

which

If fixed, only the selected covariates are extraced from the model. If missing all the covariates are extracted.

Details

A list of objects useful to run the cluster effect algorithm is created.

Value

p

The percentiles used in the quantile regression.

X

A list containing as many matrices as covariates, where for each matrix the number of columns corresponds to the number of the responses. Each column of a matrix corresponds to one curve effect. In the case of a univariate model it is a unique matrix.

Xl

A list as X. Each column of a matrix corresponds to the lower interval of the curve effect. In the case of a univariate model it is a unique matrix.

Xr

A list as X. Each column of a matrix corresponds to the upper interval of the curve effect. In the case of a univariate model it is a unique matrix.

Author(s)

Gianluca Sottile gianluca.sottile@unipa.it

See Also

clustEff, for clustering algorithm; summary.clustEff and plot.clustEff, for summarizing and plotting clustEff objects.

Examples


# using simulated data

# see the documentation for 'clustEff'


clustEff documentation built on June 28, 2022, 5:06 p.m.