Learn R Programming

stats (version 3.3.2)

SSD: SSD Matrix and Estimated Variance Matrix in Multivariate Models

Description

Functions to compute matrix of residual sums of squares and products, or the estimated variance matrix for multivariate linear models.

Usage


# S3 method for class 'mlm'
SSD(object, ...)

# S3 methods for class 'SSD' and 'mlm' estVar(object, ...)

Arguments

object
object of class "mlm", or "SSD" in the case of estVar.
Unused

Value

SSD() returns a list of class "SSD" containing the following components
SSD
The residual sums of squares and products matrix
df
Degrees of freedom
call
Copied from object
estVar returns a matrix with the estimated variances and covariances.

See Also

mauchly.test, anova.mlm

Examples

Run this code
# Lifted from Baron+Li:
# "Notes on the use of R for psychology experiments and questionnaires"
# Maxwell and Delaney, p. 497
reacttime <- matrix(c(
420, 420, 480, 480, 600, 780,
420, 480, 480, 360, 480, 600,
480, 480, 540, 660, 780, 780,
420, 540, 540, 480, 780, 900,
540, 660, 540, 480, 660, 720,
360, 420, 360, 360, 480, 540,
480, 480, 600, 540, 720, 840,
480, 600, 660, 540, 720, 900,
540, 600, 540, 480, 720, 780,
480, 420, 540, 540, 660, 780),
ncol = 6, byrow = TRUE,
dimnames = list(subj = 1:10,
              cond = c("deg0NA", "deg4NA", "deg8NA",
                       "deg0NP", "deg4NP", "deg8NP")))

mlmfit <- lm(reacttime ~ 1)
SSD(mlmfit)
estVar(mlmfit)

Run the code above in your browser using DataLab