roi_sampling_control: Generate a list of parameters for sampling from the estimated...
In ammeir2/selectiveROI:
View source: R/newMLEfunction.R
Description
A function which generates a list of parameters for use in the roiMLE function,
for sampling from the estimated distribution. This can be used for constructing
confidence intervals or conducting hypothesis testing.
Usage
1
roi_sampling_control(samp_per_chain = 0, burnin = 1000, n_chains = 5)
Arguments
samp_per_chain
the number of samples to take from the estimated
post-selection distribution in each MCMC chain. If 0, then no sampling
will be conducted (default).
burnin
the burnin periods for each MCMC chain.
n_chains
the number of MCMC chains to run. The MCMC chains use
different intializations. One chain will usually suffice, but it is
recommended to run several if there is strong depedence in the data
that may slow down the mixing of the MCMC chain.
ammeir2/selectiveROI documentation built on March 16, 2020, 1:30 a.m.
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View source: R/newMLEfunction.R
Description
A function which generates a list of parameters for use in the roiMLE function, for sampling from the estimated distribution. This can be used for constructing confidence intervals or conducting hypothesis testing.
Usage
1 | roi_sampling_control(samp_per_chain = 0, burnin = 1000, n_chains = 5)
|
Arguments
samp_per_chain |
the number of samples to take from the estimated post-selection distribution in each MCMC chain. If 0, then no sampling will be conducted (default). |
burnin |
the burnin periods for each MCMC chain. |
n_chains |
the number of MCMC chains to run. The MCMC chains use different intializations. One chain will usually suffice, but it is recommended to run several if there is strong depedence in the data that may slow down the mixing of the MCMC chain. |
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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