norm.proposal: Manage proposal functions tune variance for metropolis...

In tripEstimation: Metropolis Sampler and Supporting Functions for Estimating Animal Movement from Archival Tags and Satellite Fixes

Manage proposal functions tune variance for metropolis sampler

Description

Generate new proposals for the x from the current. Generates all x at once.

Usage

norm.proposal(m, n, sigma)

mvnorm.proposal(m, n, Sigma)

bmvnorm.proposal(m, n, Sigma)

Arguments

m	number of records
n	number of parameters
sigma	variance
Sigma	variance

Details

norm.proposal - Independent Normal proposal - every component is independent, with variances of individual components determined by sigma. The recycling rule applies to sigma, so sigma may be a scalar, an m vector or a m by n matrix.

mvnorm.proposal - Multivariate Normal proposal - all components of all points are correlated. In this case Sigma is the joint covariance of the m*n components of the proposal points.

bmvnorm.proposal - Block Multivariate Normal proposal - components of points are correlated, but points are independent. Here Sigma is an array of m covariance matrices that determine the covariance of the m proposal points.

Value

An list object with get, set and tune functions to manage the state of the proposals.

proposal	propose new set of parameters from last
get	get variance values
set	set variance values
tune	tune the variance for proposal functions

Author(s)

Simon Wotherspoon

tripEstimation documentation built on April 22, 2023, 1:11 a.m.