This package implements ridge fusion methodology for inverse covariance matrix estimation for use in quadratic discriminant analysis. The package also contains function for model based clustering using ridge fusion for inverse matrix estimation, as well as tuning parameter selection functions. We have also implemented QDA using joint inverse covariance estimation.
|Author||Bradley S. Price|
|Date of publication||2014-09-19 01:14:46|
|Maintainer||Bradley S. Price <email@example.com>|
|License||MIT + file LICENSE|
|Package repository||View on CRAN|
|Installation||Install the latest version of this package by entering the following in R:
|FusedQDA: Quadratic Discriminant Analysis with Ridge Fused Inverse...|
|RidgeFused: Ridged Fused Inverse Covariance Matrix Estimation|
|RidgeFusedCV: Ridged Fused Validation Likelihood|
|RidgeFusedQDA-class: Class '"RidgeFusedQDA"'|
|RidgeFusion-class: Class '"RidgeFusion"'|
|RidgeFusionCV-class: Class '"RidgeFusionCV"'|
|SSRidgeFused: Semis Supervised Ridge Fusion Model Based Clustering|
|SSRidgeFusedCV: Tuning Parameter Selection For Semi-Supervised Ridge Fusion...|
|SSRidgeFusion-class: Class '"SSRidgeFusion"'|
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