Description Usage Arguments Value Author(s) References See Also Examples
The functions cooks.distance.mlm
and hatvalues.mlm
are designed as extractor functions for regression deletion
diagnostics for multivariate linear models following Barrett & Ling (1992).
These are close analogs of
methods for univariate and generalized linear models handled by the
influence.measures
in the stats
package.
In addition, the functions provide diagnostics for deletion of
subsets of observations of size m>1
.
1 2 3 4 5 | ## S3 method for class 'mlm'
cooks.distance(model, infl = mlm.influence(model, do.coef = FALSE), ...)
## S3 method for class 'mlm'
hatvalues(model, m = 1, infl, ...)
|
model |
A |
do.coef |
logical. Should the coefficients be returned in the |
m |
Size of the subsets for deletion diagnostics |
infl |
An influence structure, of class |
... |
Other arguments, passed on |
When m=1
, these functions return a vector, corresponding to the observations
in the data set.
When m>1
, they return a list of m \times m matrices,
corresponding to deletion of subsets of size m
.
Michael Friendly
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.
influencePlot.mlm
, ~~~
1 2 3 4 5 6 7 |
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