GR_est {rlme}

GR Method

Description

Fits a model using the GR method

Usage

GR_est(x, y, I, sec, mat, school, section, rprpair = "hl-disp",
  verbose = FALSE)

Arguments

x

Covariate matrix or data frame.

y

Response matrix or data frame.

I

Number of clusters

sec

A vector of subcluster numbers in clusters.

mat

A matrix of numbers of observations in subclusters. Dimension is Ixmax(number ofsubclusters). Each row indicates one cluster.

school

A vector of clusters, nx1.

section

A vector of subclusters, nx1.

rprpair

By default, it uses "hl-disp" in the random prediction procedure (RPP). Also, "med-mad" would be an alternative.

verbose

Boolean indicating whether to print out messages from the algorithm.

Value

theta

Fixed effect estimates.

ses

Standard error for the fixed esimates.

sigma

Variances of cluster, subcluster, and residual.

ehat

Raw error.

ehats

Independence error from last weighted step.

effect_sch

Cluster random error.

effect_sec

Subcluster random error.

effect_err

Epsilon error.

Author(s)

Yusuf Bilgic

Examples

# See rlme function