ashr (version 0.9.2)

calc_loglik: Compute loglikelihood for data from ash fit

Description

Return the log-likelihood of the data betahat, with standard errors betahatsd, under the fitted distribution in the ash object.

Usage

calc_loglik(a, betahat, betahatsd, df, model = c("EE", "ES"), alpha = 0)

Arguments

a

the fitted ash object

betahat

the data

betahatsd

the observed standard errors

df

appropriate degrees of freedom for (t) distribution of betahat/sebetahat

model

indicates whether you want the likelihood under the EE or ES model

alpha

a scalar performing transformation on betahat and sebetahat, such that the model is $\beta_j / s_j^alpha ~ g()$,and eqnbetahat_j / s_j^alpha ~ N(0,(sebetahat^(1-alpha))^2) or student t distribution. When $alpha=0$ we have the EE model, when $alpha=1$, we have the ES model. $alpha$ should be in between 0 and 1, inclusively. Default is alpha=0.

Details

See example in CompareBetahatvsZscoreAnalysis.rmd