rt0,numeric,dual-method

positive integer; the number of samples.

A dual number; the degree of freedom.

Simulate random variates from the student-t distribution

Implements the forward-mode automatic differentiation for
multivariate functions using the matrix-calculus notation from Magnus and
Neudecker (2019) <doi:10.1002/9781119541219>. Two key features of the package
are: (i) it incorporates various optimisation strategies to improve performance;
this includes applying memoisation to cut down object construction time, using
sparse matrix representation to speed up derivative calculation, and creating
specialised matrix operations to reduce computation time; (ii) it supports
differentiating random variates with respect to their parameters, targeting
Markov chain Monte Carlo (MCMC) and general simulation-based applications.

Chun Fung Kwok

ADtools

rt0,numeric,dual-method: Simulate random variates from the student-t distribution

Description

Usage

Arguments