msir v1.3.1
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Model-Based Sliced Inverse Regression
An R package for dimension reduction based on finite Gaussian mixture modeling of inverse regression.
Functions in msir
| Name | Description | |
| plot.msir | Plot method for 'msir' objects. | |
| msir.permutation.test | Permutation test for dimensionality | |
| loess.sd | Local Polynomial Regression Fitting with Variability bands | |
| msir-package | Model-based Sliced Inverse Regression (MSIR) | |
| summary.msir | Summary and print methods for 'msir' objects | |
| msir.slices | Slice a vector into slices of approximately equal size | |
| msir.regularizedSigma | Regularized estimate of predictors covariance matrix. | |
| msir.dir | Model-based Sliced Inverse Regression directions | |
| msir.nslices | Default number of slices | |
| msir.bic | BIC-type criterion for dimensionality | |
| msir | Model-based Sliced Inverse Regression (MSIR) | |
| msir-internal | Internal 'msir' functions | |
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Details
| Type | Package |
| Date | 2016-04-07 |
| License | GPL (>= 2) |
| Repository | CRAN |
| ByteCompile | true |
| LazyLoad | yes |
| NeedsCompilation | no |
| Packaged | 2016-04-07 09:38:15 UTC; luca |
| Date/Publication | 2016-04-07 14:06:05 |
| depends | base (>= 3.0) , mclust (>= 5.0) , R (>= 3.0) |
| imports | graphics , grDevices , rgl , stats , utils |
| Contributors | Luca Scrucca |
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