ic.infer | R Documentation |
Package ic.infer
implements estimation and testing for multivariate normal
expectations with linear equality- and inequality constraints. This also includes
inference on linear models with linear equality- and inequality constraints on the
parameters. Decomposition of R-squared is also included for these models.
Function ic.est
estimates the constrained expectation of a multivariate normal
random vector, function ic.test
conducts related tests.
Function orlm
estimates constrained parameters in normal linear models based on
a linear model object or a covariance matrix. The function offers the possibility of
bootstrapping the estimates. Tests and confidence intervals are provided by a summary
function.
Function or.relimp
decomposes the $R^2$-values analogously to metric
lmg
in package relaimpo for unconstrained linear models.
However, or.relimp
is far less comfortable
to use und subject to severe limitations, since automatic selection of restrictions
for sub models is not in all cases trivial.
The package makes use of various other R packages: quadprog is used for
constrained estimation, mvtnorm in calculation of weights for null distributions
of test statistics, kappalab for averaging over orderings in function or.relimp
,
and boot for bootstrapping.
The theory behind inequality-constrained estimation and testing as well as
functionality of the package are explained in a vignette (Link from within dynamic help:
../doc/ic.infer.pdf) that is based on Groemping (2010).
The vignette can also be opened from the command line by vignette("ic.infer")
.
The output of function ic.est
belongs to S3 class orest
.
The output of function ic.test
belongs to S3 class ict
.
The output of function orlm
belongs to S3 classes orlm
and orest
.
All these classes offer print and summary methods.
The output of function or.relimp
is a named vector.
This package uses as an internal function the function nchoosek
from vsn,
authored by Wolfgang Huber, available under LGPL.
It also uses modifications of numerical routines that were provided by John Fox in R-help.
Thanks go to Wiley for permission of incorporating the grades data from Table 1.3.1 of Robertson, Wright and Dykstra (1988) into the package.
Ulrike Groemping, BHT Berlin
Groemping, U. (2010). Inference With Linear Equality And Inequality Constraints Using R: The Package ic.infer. Journal of Statistical Software, Forthcoming.
Kudo, A. (1963). A multivariate analogue of the one-sided test. Biometrika 50, 403–418
Robertson T, Wright F, Dykstra R (1988). Order-Restricted Inference. Wiley, New York.
Sasabuchi, S. (1980) A test of a multivariate normal mean with composite hypotheses determined by linear inequalities. Biometrika 67, 429–429
Shapiro, A. (1988). Towards a unified theory of inequality-constrained testing in multivariate analysis. International Statistical Review 56, 49–62
Silvapulle, M.J. and Sen, P.K. (2004). Constrained Statistical Inference. Wiley, New York
See also ic.est
, ic.test
, orlm
,
or.relimp
, packages boot, kappalab,
mvtnorm, quadprog, and relaimpo
## unrestricted linear model for grade point averages
limo <- lm(meanGPA~.-n, weights=n, data=grades)
summary(limo)
## restricted linear model with restrictions that better HSR ranking
## cannot deteriorate meanGPA
orlimo <- orlm(lm(meanGPA~.-n, weights=n, data=grades), index=2:9,
ui=make.mon.ui(grades$HSR))
summary(orlimo, brief=TRUE)
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