sparsediscrim: Sparse and Regularized Discriminant Analysis

A collection of sparse and regularized discriminant analysis methods intended for small-sample, high-dimensional data sets. The package features the High-Dimensional Regularized Discriminant Analysis classifier.

AuthorJohn A. Ramey <johnramey@gmail.com>
Date of publication2016-06-24 19:14:14
MaintainerJohn A. Ramey <johnramey@gmail.com>
LicenseMIT + file LICENSE
Version0.2.3
https://github.com/ramhiser/sparsediscrim
http://ramhiser.com

View on CRAN

Man pages

center_data: Centers the observations in a matrix by their respective...

cov_autocorrelation: Generates a p \times p autocorrelated covariance matrix

cov_block_autocorrelation: Generates a p \times p block-diagonal covariance matrix with...

cov_eigen: Computes the eigenvalue decomposition of the maximum...

cov_intraclass: Generates a p \times p intraclass covariance matrix

cov_list: Computes the covariance-matrix maximum likelihood estimators...

cov_mle: Computes the maximum likelihood estimator for the sample...

cov_pool: Computes the pooled maximum likelihood estimator (MLE) for...

cov_shrink_diag: Computes a shrunken version of the maximum likelihood...

cv_partition: Randomly partitions data for cross-validation.

diag_estimates: Computes estimates and ancillary information for diagonal...

dlda: Diagonal Linear Discriminant Analysis (DLDA)

dmvnorm_diag: Computes multivariate normal density with a diagonal...

dqda: Diagonal Quadratic Discriminant Analysis (DQDA)

generate_blockdiag: Generates data from 'K' multivariate normal data populations,...

generate_intraclass: Generates data from 'K' multivariate normal data populations,...

h: Bias correction function from Pang et al. (2009).

hdrda: High-Dimensional Regularized Discriminant Analysis (HDRDA)

hdrda_cv: Helper function to optimize the HDRDA classifier via...

lda_pseudo: Linear Discriminant Analysis (LDA) with the Moore-Penrose...

lda_schafer: Linear Discriminant Analysis using the Schafer-Strimmer...

lda_thomaz: Linear Discriminant Analysis using the Thomaz-Kitani-Gillies...

log_determinant: Computes the log determinant of a matrix.

mdeb: The Minimum Distance Empirical Bayesian Estimator (MDEB)...

mdmeb: The Minimum Distance Rule using Modified Empirical Bayes...

mdmp: The Minimum Distance Rule using Moore-Penrose Inverse (MDMP)...

no_intercept: Removes the intercept term from a formula if it is included

plot.hdrda_cv: Plots a heatmap of cross-validation error grid for a HDRDA...

posterior_probs: Computes posterior probabilities via Bayes Theorem under...

print.dlda: Outputs the summary for a DLDA classifier object.

print.dqda: Outputs the summary for a DQDA classifier object.

print.hdrda: Outputs the summary for a HDRDA classifier object.

print.lda_pseudo: Outputs the summary for a lda_pseudo classifier object.

print.lda_schafer: Outputs the summary for a lda_schafer classifier object.

print.lda_thomaz: Outputs the summary for a lda_thomaz classifier object.

print.mdeb: Outputs the summary for a MDEB classifier object.

print.mdmeb: Outputs the summary for a MDMEB classifier object.

print.mdmp: Outputs the summary for a MDMP classifier object.

print.sdlda: Outputs the summary for a SDLDA classifier object.

print.sdqda: Outputs the summary for a SDQDA classifier object.

print.smdlda: Outputs the summary for a SmDLDA classifier object.

print.smdqda: Outputs the summary for a SmDQDA classifier object.

quadform: Quadratic form of a matrix and a vector

quadform_inv: Quadratic Form of the inverse of a matrix and a vector

rda_cov: Calculates the RDA covariance-matrix estimators for each...

rda_weights: Computes the observation weights for each class for the HDRDA...

regdiscrim_estimates: Computes estimates and ancillary information for regularized...

risk_stein: Stein Risk function from Pang et al. (2009).

sdlda: Shrinkage-based Diagonal Linear Discriminant Analysis (SDLDA)

sdqda: Shrinkage-based Diagonal Quadratic Discriminant Analysis...

smdlda: Shrinkage-mean-based Diagonal Linear Discriminant Analysis...

smdqda: Shrinkage-mean-based Diagonal Quadratic Discriminant Analysis...

solve_chol: Computes the inverse of a symmetric, positive-definite matrix...

tong_mean_shrinkage: Tong et al. (2012)'s Lindley-type Shrunken Mean Estimator

update_hdrda: Helper function to update tuning parameters for the HDRDA...

var_shrinkage: Shrinkage-based estimator of variances for each feature from...

Files in this package

sparsediscrim
sparsediscrim/tests
sparsediscrim/tests/testthat.r
sparsediscrim/tests/testthat
sparsediscrim/tests/testthat/test-sdqda.r
sparsediscrim/tests/testthat/test-smdlda.r
sparsediscrim/tests/testthat/test-mdmeb.r
sparsediscrim/tests/testthat/test-sdlda.r
sparsediscrim/tests/testthat/test-lda_thomaz.r
sparsediscrim/tests/testthat/test-hdrda.r
sparsediscrim/tests/testthat/test-lda_schafer.r
sparsediscrim/tests/testthat/test-mdmp.r
sparsediscrim/tests/testthat/test-smdqda.r
sparsediscrim/tests/testthat/test-lda_pseudo.r
sparsediscrim/tests/testthat/test-mdeb.r
sparsediscrim/tests/testthat/test-data-block-autocorrelation.r
sparsediscrim/tests/testthat/test-dqda.r
sparsediscrim/tests/testthat/test-dlda.r
sparsediscrim/NAMESPACE
sparsediscrim/NEWS
sparsediscrim/R
sparsediscrim/R/dlda.r
sparsediscrim/R/sdqda.r
sparsediscrim/R/lda-thomaz.r
sparsediscrim/R/data-intraclass.r
sparsediscrim/R/lda-pseudo.r
sparsediscrim/R/smdlda.r
sparsediscrim/R/smdqda.r
sparsediscrim/R/estimates.r
sparsediscrim/R/tong-shrinkage.r
sparsediscrim/R/mdmp.r
sparsediscrim/R/hdrda.r
sparsediscrim/R/stein-shrinkage.r
sparsediscrim/R/helper-intercept.r
sparsediscrim/R/mdmeb.r
sparsediscrim/R/dqda.r
sparsediscrim/R/helper-cov.r
sparsediscrim/R/helper-cv.r
sparsediscrim/R/data-block-autocorrelation.r
sparsediscrim/R/sdlda.r
sparsediscrim/R/lda-schafer.r
sparsediscrim/R/helper.r
sparsediscrim/R/mdeb.r
sparsediscrim/README.md
sparsediscrim/MD5
sparsediscrim/DESCRIPTION
sparsediscrim/man
sparsediscrim/man/sdlda.Rd sparsediscrim/man/cov_intraclass.Rd sparsediscrim/man/mdmp.Rd sparsediscrim/man/cov_block_autocorrelation.Rd sparsediscrim/man/hdrda.Rd sparsediscrim/man/log_determinant.Rd sparsediscrim/man/dqda.Rd sparsediscrim/man/plot.hdrda_cv.Rd sparsediscrim/man/quadform_inv.Rd sparsediscrim/man/sdqda.Rd sparsediscrim/man/dmvnorm_diag.Rd sparsediscrim/man/print.smdqda.Rd sparsediscrim/man/print.dlda.Rd sparsediscrim/man/h.Rd sparsediscrim/man/var_shrinkage.Rd sparsediscrim/man/print.lda_pseudo.Rd sparsediscrim/man/diag_estimates.Rd sparsediscrim/man/print.hdrda.Rd sparsediscrim/man/no_intercept.Rd sparsediscrim/man/print.smdlda.Rd sparsediscrim/man/print.mdmp.Rd sparsediscrim/man/cov_shrink_diag.Rd sparsediscrim/man/smdqda.Rd sparsediscrim/man/quadform.Rd sparsediscrim/man/mdmeb.Rd sparsediscrim/man/hdrda_cv.Rd sparsediscrim/man/lda_pseudo.Rd sparsediscrim/man/print.dqda.Rd sparsediscrim/man/cov_pool.Rd sparsediscrim/man/cov_mle.Rd sparsediscrim/man/generate_blockdiag.Rd sparsediscrim/man/center_data.Rd sparsediscrim/man/cov_eigen.Rd sparsediscrim/man/dlda.Rd sparsediscrim/man/print.mdmeb.Rd sparsediscrim/man/solve_chol.Rd sparsediscrim/man/print.mdeb.Rd sparsediscrim/man/print.sdlda.Rd sparsediscrim/man/risk_stein.Rd sparsediscrim/man/rda_cov.Rd sparsediscrim/man/cov_autocorrelation.Rd sparsediscrim/man/cv_partition.Rd sparsediscrim/man/print.sdqda.Rd sparsediscrim/man/lda_schafer.Rd sparsediscrim/man/tong_mean_shrinkage.Rd sparsediscrim/man/generate_intraclass.Rd sparsediscrim/man/mdeb.Rd sparsediscrim/man/print.lda_thomaz.Rd sparsediscrim/man/regdiscrim_estimates.Rd sparsediscrim/man/smdlda.Rd sparsediscrim/man/cov_list.Rd sparsediscrim/man/lda_thomaz.Rd sparsediscrim/man/rda_weights.Rd sparsediscrim/man/update_hdrda.Rd sparsediscrim/man/posterior_probs.Rd sparsediscrim/man/print.lda_schafer.Rd
sparsediscrim/LICENSE

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

All documentation is copyright its authors; we didn't write any of that.