Description Usage Arguments Details Value Author(s) References See Also Examples
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.
1 | mlm.influence(model, do.coef = TRUE, m = 1, ...)
|
model |
An |
do.coef |
logical. Should the coefficients be returned in the |
m |
Size of the subsets for deletion diagnostics |
... |
Further arguments passed to other methods |
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.
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 |
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 |
labels |
Observation labels |
call |
Model call for the |
Beta |
Deletion regression coefficients– included if |
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.
Barrett, B. E. (2003). Understanding Influence in Multivariate Regression. Communications in Statistics – Theory and Methods, 32, 3, 667-680.
influencePlot.mlm
, ~~~
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