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hitandrun (version 0.5-6)

"Hit and Run" and "Shake and Bake" for Sampling Uniformly from Convex Shapes

Description

The "Hit and Run" Markov Chain Monte Carlo method for sampling uniformly from convex shapes defined by linear constraints, and the "Shake and Bake" method for sampling from the boundary of such shapes. Includes specialized functions for sampling normalized weights with arbitrary linear constraints. Tervonen, T., van Valkenhoef, G., Basturk, N., and Postmus, D. (2012) . van Valkenhoef, G., Tervonen, T., and Postmus, D. (2014) .

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install.packages('hitandrun')

Monthly Downloads

2,208

Version

0.5-6

License

GPL-3

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Maintainer

Gert Valkenhoef

Last Published

May 27th, 2022

Functions in hitandrun (0.5-6)

findExtremePoints

Find extreme points
createBoundBox

Calculate a bounding box
findFace

Find the closest face (constraint) to an interior point of a polytope.
findInteriorPoint

Find an interior point
findVertices

Find vertices of the polytope
createSeedPoint

Generate a seed point
eliminateRedundant

Eliminate redundant linear constraints
createTransform

Create transformation matrices
bbReject

Bounding box rejection sampler
harConstraints

Constraint formulation utility functions
har

"Hit and Run" sampler
hitandrun

"Hit and Run" sampler
hitandrun-package

"Hit and Run" sampling
hypersphere.sample

Sample uniformly from an n-hypersphere
shakeandbake

"Shake and Bake" sampler
sab

"Shake and Bake" sampler
transformConstraints

Apply a transformation to a set of linear constraints.
simplex.createTransform

Transform points on an (n-1)-simplex to n-dimensional space
simplex.createConstraints

Create constraints that define the (n-1)-simplex
simplex.sample

Sample uniformly from a simplex
solution.basis

Calculate the basis for the solution space of a system of linear equations