R: Methods for Adaptive Shrinkage, using Empirical Bayes

# Methods for Adaptive Shrinkage, using Empirical Bayes

## Documentation for package ‘ashr’ version 2.2-63

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS

## Help Pages

A C D E G I L M N P Q S T U V W

ashr-package | ashr

## -- A --

ash | Adaptive Shrinkage
ash.workhorse | Adaptive Shrinkage
ashci | Credible Interval Computation for the ash object
ashr | ashr
ash_pois | Performs adaptive shrinkage on Poisson data

## -- C --

calc_loglik | Compute loglikelihood for data from ash fit
calc_logLR | Compute loglikelihood ratio for data from ash fit
calc_mixmean | Generic function of calculating the overall mean of the mixture
calc_mixsd | Generic function of calculating the overall standard deviation of the mixture
calc_null_loglik | Compute loglikelihood for data under null that all beta are 0
calc_null_vloglik | Compute vector of loglikelihood for data under null that all beta are 0
calc_vloglik | Compute vector of loglikelihood for data from ash fit
calc_vlogLR | Compute vector of loglikelihood ratio for data from ash fit
cdf.ash | cdf method for ash object
cdf_conv | cdf_conv
cdf_post | cdf_post
compute_lfsr | Function to compute the local false sign rate
comp_cdf | Generic function of computing the cdf for each component
comp_cdf_conv | comp_cdf_conv
comp_cdf_conv.normalmix | comp_cdf_conv.normalmix
comp_cdf_conv.unimix | cdf of convolution of each component of a unif mixture
comp_cdf_post | comp_cdf_post
comp_dens | Generic function of calculating the component densities of the mixture
comp_dens_conv | comp_dens_conv
comp_dens_conv.normalmix | comp_dens_conv.normalmix
comp_dens_conv.unimix | density of convolution of each component of a unif mixture
comp_mean | Generic function of calculating the first moment of components of the mixture
comp_mean.normalmix | comp_mean.normalmix
comp_mean.tnormalmix | comp_mean.tnormalmix
comp_mean2 | Generic function of calculating the second moment of components of the mixture
comp_postmean | comp_postmean
comp_postmean2 | comp_postmean2
comp_postprob | comp_postprob
comp_postsd | comp_postsd
comp_sd | Generic function to extract the standard deviations of components of the mixture
comp_sd.normalmix | comp_sd.normalmix
comp_sd.tnormalmix | comp_sd.normalmix
cxxMixSquarem | Brief description of function.

## -- D --

dens | Find density at y, a generic function
dens_conv | dens_conv
dlogf | The log-F distribution

## -- E --

estimate_mixprop | Estimate mixture proportions of a mixture g given noisy (error-prone) data from that mixture.

## -- G --

gen_etruncFUN | gen_etruncFUN
get_density | Density method for ash object
get_fitted_g | Return lfsr from an ash object
get_lfdr | Return lfsr from an ash object
get_lfsr | Return lfsr from an ash object
get_loglik | Return lfsr from an ash object
get_logLR | Return lfsr from an ash object
get_np | Return lfsr from an ash object
get_pi0 | Return lfsr from an ash object
get_pm | Return lfsr from an ash object
get_post_sample | Sample from posterior
get_pp | Return lfsr from an ash object
get_psd | Return lfsr from an ash object
get_qvalue | Return lfsr from an ash object
get_svalue | Return lfsr from an ash object

## -- I --

igmix | Constructor for igmix class

## -- L --

lik_binom | Likelihood object for Binomial error distribution
lik_logF | Likelihood object for logF error distribution
lik_normal | Likelihood object for normal error distribution
lik_normalmix | Likelihood object for normal mixture error distribution
lik_pois | Likelihood object for Poisson error distribution
lik_t | Likelihood object for t error distribution
loglik_conv | loglik_conv
loglik_conv.default | loglik_conv.default
log_comp_dens_conv | log_comp_dens_conv
log_comp_dens_conv.normalmix | log_comp_dens_conv.normalmix
log_comp_dens_conv.unimix | log density of convolution of each component of a unif mixture

## -- M --

mixcdf | mixcdf
mixcdf.default | mixcdf.default
mixEM | Estimate mixture proportions of a mixture model by EM algorithm
mixIP | Estimate mixture proportions of a mixture model by Interior Point method
mixmean2 | Generic function of calculating the overall second moment of the mixture
mixprop | Generic function of extracting the mixture proportions
mixSQP | Estimate mixture proportions of a mixture model using mix-SQP algorithm.
mixVBEM | Estimate posterior distribution on mixture proportions of a mixture model by a Variational Bayes EM algorithm
my_e2truncbeta | second moment of truncated Beta distribution
my_e2truncgamma | second moment of truncated gamma distribution
my_e2truncnorm | Expected Squared Value of Truncated Normal
my_e2trunct | my_e2trunct
my_etruncbeta | mean of truncated Beta distribution
my_etruncgamma | mean of truncated gamma distribution
my_etrunclogf | my_etrunclogf
my_etruncnorm | Expected Value of Truncated Normal
my_etrunct | my_etrunct
my_vtruncnorm | Variance of Truncated Normal

## -- N --

ncomp | ncomp
ncomp.default | ncomp.default
normalmix | Constructor for normalmix class

## -- P --

pcdf_post | pcdf_post
plogf | The log-F distribution
plot.ash | Plot method for ash object
plot_diagnostic | Diagnostic plots for ash object
pm_on_zero | Generic function to extract which components of mixture are point mass on 0
posterior_dist | Compute Posterior
postmean | postmean
postmean2 | postmean2
postsd | postsd
post_sample | post_sample
post_sample.normalmix | post_sample.normalmix
post_sample.unimix | post_sample.unimix
print.ash | Print method for ash object
prune | prune

## -- Q --

qval.from.lfdr | Function to compute q values from local false discovery rates

## -- S --

set_data | Takes raw data and sets up data object for use by ash
summary.ash | Summary method for ash object

## -- T --

tnormalmix | Constructor for tnormalmix class

## -- U --

unimix | Constructor for unimix class

## -- V --

vcdf_post | vcdf_post

## -- W --

w_mixEM | Estimate mixture proportions of a mixture model by EM algorithm (weighted version)