likelihood: Calculate likelihood of data under model

In debruine/bfrr: Bayes Factors and Robustness Regions

Description

Calculate likelihood of data under model

Usage

likelihood(sample_mean = 0, sample_se = 0.1, sample_df = 99,
  model = c("H0", "normal", "uniform"), ..., steps = 2000)

Arguments

sample_mean	the observed sample mean
sample_se	the observed sample standard error
sample_df	the observed sample degrees of freedom
model	the model under which to calculate likelihood (H0, normal or uniform
...	model parameters (mean, sd and tail for normal, lower and upper for uniform)
steps	the number of steps to integrate over

Value

double

Examples

lNull <- likelihood(0.5, 1/sqrt(30), 29, "H0")
lTheory <- likelihood(0.5, 1/sqrt(30), 29, "normal", mean = 0, sd = 1, tail = 1)
BayesFactor <- lNull/lTheory

debruine/bfrr documentation built on March 7, 2020, 5:47 p.m.