Man pages for dcgerard/succotashr
Surrogate and Confounder Correction Occuring Together with Adaptive Shrinkage

draw_betaDraw from a mixture of normals.
dt_wrapWrapper for dt with a non-zero mena and non-1 standard...
factor_mleRegularized maximum likelihood factor analysis with...
fit_succotash_unif_coordCoordinate ascent algorithm for normal likelihood and...
fn_abFunction to optimize wrt alpha and beta
fn_lFunction to minimize wrt the loadings.
fun_scaleObjective function in intermediate step of EM algorithm when...
fun_unif_scaleCriterion function for the scale parameter as an intermediate...
f_valRegularized normal log-likelihood.
get_pdiffsCalculate the difference in cdfs.
gr_abGradient of function to optimize wrt alpha and beta.
gr_lGradient of function to minimize wrt loadings.
lfdr_to_qTransform local false discovery rates to q-values.
llike_unif_simpMe being as careful as possible when calculating the...
minus_trigammaTrigamma minus a constant.
mod_faModerated factor analysis. Optimize over loadings, factors,...
normal_coordCoordinate ascent for normal mixtures with normal likelihood.
normal_llike_gradGradient of the log-likelihood wrt Z.
normal_llike_simpMe being super careful in calculating the normal mixtures...
normal_only_zWrapper for 'succotash_llike', but useful when calling optim.
only_ZWrapper for 'succotash_llike_unif' but useful for optim where...
only_Z_gradWrapper for 'unif_grad_simp', but useful for optim where only...
pca_naiveBasic PCA.
pca_shrinkvarUse PCA to estimate confounders, then shrink variances using...
pt_wrapWrapper for pt with a non-zero mena and non-1 standard...
succotashSurrogate and Confounder Correction Occuring Together with...
succotash_emAn EM algorithm for maximizing the SUCCOTASH log-likelihood.
succotash_fixedA fixed-point iteration of the EM algorithm.
succotash_given_alphaMaximize the SUCCOTASH log-likelihood and return posterior...
succotash_llikeThe SUCCOTASH log-likelihood.
succotash_llike_unifCalculates the loglikelihood of the SUCCOTASH model under...
succotashr'succotashr': An 'R' package for running Surrogate and...
succotash_summariesProvides posterior summaries in the SUCCOTASH model.
succotash_unif_fixedA fixed point iteration in the mixture of uniforms EM.
tfunFunction to optimize over Z in EM step.
tgradGradient of function to optimize over Z in EM step.
trimTruncates small numbers to 0.
t_succotash_llike_unifCalculates the loglikelihood of the SUCCOTASH model under...
t_succotash_unif_fixedA fixed point iteration in the mixture of uniforms EM and a...
t_unif_emEM algorithm for uniform mixtures and t-likelihood
t_uniform_succ_given_alphaSecond step of SUCCOTASH with uniform mixture and a...
tupdate_piEM step to update pi
unif_grad_llikeMy first attempt at calculating the gradient of the...
unif_grad_simpThis is me being very careful about calculating the gradient...
uniform_succ_emEM algorithm for second step of SUCCOTASH
uniform_succ_given_alphaSecond step of SUCCOTASH with uniform mixture.
unif_update_piE step in EM algorithm.
unif_update_zRuns a few newton steps to update Z given scale_val.
update_AUpdate low rank mean in regularized maximum likelihood factor...
update_abUpdates the hyperparameters for the gamma prior.
update_fUpdate the factors given the loadings and the data matrix.
update_lUpdate the loadings given the factors, the data matrix, and...
update_sigmaUpdate variances in regularized maximum likelihood factor...
dcgerard/succotashr documentation built on May 12, 2017, 9:48 p.m.