vbglmss.mixedSS: Variational approximation of Spike and Slab regression

Description Usage Arguments Value

Description

The function fits a regression model where observations can be from logistic and/or gaussian likelihood. The coefficients are shared, and can have Spike and Slab (SS) and/or Gaussian (G) priors.

Usage

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  vbglmss.mixedSS(y, Xy, Zy, h, Xh, Zh,
    prior = list(theta = list(), beta = list(), binary = list(), gaussian = list()),
    verbose = FALSE, damp = 0, eps = 0.01, max.iter = 100)

Arguments

y

Binary observations

Xy

SS covariates for y

Zy

G covariates for y

h

Gaussian observations

Xh

SS covariates for h

Zh

G covariates for h

prior

A list of priors. See details.

verbose

print additional runtime messages

damp

Damping coefficient in SS mean update. damp * old + (1-damp)*new.

eps

the approximation loop convergence threshold

max.iter

– TODO

Value

A list with posteriors.


antiphon/vbss documentation built on May 10, 2019, 12:22 p.m.