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- dist-class: A class representing a probability distribution
A class representing a probability distribution
Description
This class represents a probability distribution.
See make.dist
for more information.
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- adaptive.metropolis.sample: Adaptive Metropolis
- ar.act: Compute the autocorrelation time of a chain
- arms.sample: Adaptive Rejection Metropolis Sampler
- check.dist.gradient: Test a gradient function
- chud: Cholesky Update/Downdate
- compare.samplers: Compare MCMC samplers on distributions
- comparison.plot: Plot the results of compare.samplers
- compounded.sampler: Build a sampler from transition functions
- cov.match.sample: Sample with covariance-matching slice sampling
- dist-class: A class representing a probability distribution
- funnel.dist: Funnel distribution object
- hyperrectangle.sample: Multivariate slice samplers
- make.c.dist: Define a probability distribution object with C log-density
- make.cone.dist: Create a cone distribution object
- make.dist: Define a probability distribution object
- make.gaussian: Gaussian distribution objects
- make.multimodal.dist: Create a distribution object for a random mixture of...
- make.mv.gamma.dist: Create a distribution object for a set of uncorrelated Gamma...
- multivariate.metropolis.sample: Metropolis samplers
- nonadaptive.crumb.sample: Sample with nonadaptive-crumb slice sampling
- oblique.hyperrect.sample: Eigendecomposition-based hyperrectangle method
- raw.symbol: Locate a symbol
- SamplerCompare-package: A Framework for Comparing the Performance of MCMC Samplers
- schools.dist: Eight schools distribution object
- shrinking.rank.sample: Sample with shrinking-rank slice sampling
- simulation.result: Summarize one MCMC chain
- stepout.slice.sample: Univariate slice samplers
- twonorm: Euclidean norm of a vector
- univar.eigen.sample: Eigendecomposition-based slice samplers
- wrap.c.sampler: Create an R stub function for a sampler implemented in C