Methods for Adaptive Shrinkage, using Empirical Bayes

Documentation for package ‘ashr’ version 2.2-63

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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

-- W --

w_mixEM

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