likelihood: Calculate Log-Likelihood

In TasCL/ggdmc: Dynamic Model of Choice with Parallel Computation, and C++ Capabilities

Description

likelihood.rd is a legacy function for computing diffusion model density. If the speed of computation is a concern, the user may want to use ddmc, which implemnts a streamlined C++ diffusion model density.

Usage

likelihood(data, p.vector, min.like = 1e-10, ...)

## Default S3 method:
likelihood(data, p.vector, min.like = 1e-10, ...)

## S3 method for class 'rd'
likelihood(data, p.vector, min.like = 1e-10, ...)

## S3 method for class 'norm'
likelihood(data, p.vector, min.like = 1e-10, ...)

Arguments

data	a model data instance
p.vector	a parameter vector
min.like	minimal likelihood, 1e-10
...	other parameters, such as precision for ddm, ok.types for lba_B.

Value

a vector of likelihoods for each RT in data (in same order)

TasCL/ggdmc documentation built on May 9, 2019, 4:19 p.m.