# 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.

Author
John A. Ramey <johnramey@gmail.com>
Date of publication
2016-06-24 19:14:14
Maintainer
John A. Ramey <johnramey@gmail.com>
Version
0.2.3
URLs

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
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.
Quadratic form of a matrix and a vector
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
smdlda
Shrinkage-mean-based Diagonal Linear Discriminant Analysis...
smdqda