ghk_obs_vectorise: GHK algorithm (vectorised)
In lolmid/unbiased_intractable_targets: Debiased particle MCMC with couplings
Description
runs the GHK algorithm to obtain importance sampling estimates for the observations
Usage
1
ghk_obs_vectorise(nsamp, y_obs, mean_mat, uniform_rvs, Sigma, K_units = NULL)
Arguments
nsamp
number of particles x dimension of each observation
y_obs
matrix of observations, nobs x dimension of each observation
mean_mat
matrix of means for each observation in y_obs
uniform_rvs
nobs x nsamp uniform random numbers
Sigma
covariance matrix used in logistic regression
lolmid/unbiased_intractable_targets documentation built on May 13, 2019, 11:54 p.m.
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Description
runs the GHK algorithm to obtain importance sampling estimates for the observations
Usage
1 | ghk_obs_vectorise(nsamp, y_obs, mean_mat, uniform_rvs, Sigma, K_units = NULL)
|
Arguments
nsamp |
number of particles x dimension of each observation |
y_obs |
matrix of observations, nobs x dimension of each observation |
mean_mat |
matrix of means for each observation in y_obs |
uniform_rvs |
nobs x nsamp uniform random numbers |
Sigma |
covariance matrix used in logistic regression |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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