R: Calculate Regression Deletion Diagnostics for Multivariate...
mlm.influence
R Documentation
Calculate Regression Deletion Diagnostics for Multivariate Linear Models
Description
mlm.influence is the main computational function in this package.
It is usually not called directly, but rather via its alias,
influence.mlm, the S3 method for a mlm object.
Usage
mlm.influence(model, do.coef = TRUE, m = 1, ...)
Arguments
model
An mlm object, as returned by lm
do.coef
logical. Should the coefficients be returned in the inflmlm object?
m
Size of the subsets for deletion diagnostics
...
Further arguments passed to other methods
Details
The computations and methods for the m=1 case are straight-forward,
as are the computations for the m>1 case. Associated methods for
m>1 are still under development.
Value
mlm.influence returns an S3 object of class inflmlm, a list with the following components
m
Deletion subset size
H
Hat values, H_I. If m=1, a vector of diagonal entries of the ‘hat’ matrix.
Otherwise, a list of m \times m matrices corresponding to the subsets.
Q
Residuals, Q_I.
CookD
Cook's distance values
L
Leverage components
R
Residual components
subsets
Indices of the observations in the subsets of size m
labels
Observation labels
call
Model call for the mlm object
Beta
Deletion regression coefficients– included if do.coef=TRUE
Author(s)
Michael Friendly
References
Barrett, B. E. and Ling, R. F. (1992).
General Classes of Influence Measures for Multivariate Regression.
Journal of the American Statistical Association, 87(417), 184-191.
Barrett, B. E. (2003). Understanding Influence in Multivariate Regression.
Communications in Statistics – Theory and Methods, 32, 3, 667-680.