acfMCMC: Autocorrelation function for the likelihood or posterior...
In AnaCoDa: Analysis of Codon Data under Stationarity using a Bayesian Framework
Description
Usage
Arguments
See Also
View source: R/plotMCMCAlgorithmObject.R
Description
The function calculates and by defaults plots the acf and estimates the autocorrelation in the trace.
Usage
1
Arguments
mcmc
object of class MCMC
type
"LogPosterior" or "LogLikelihood", defaults to "LogPosterior"
samples
number of samples at the end of the trace used to calculate the acf
lag.max
Maximum amount of lag to calculate acf. Default is 10*log10(N), where N i the number of observations.
plot
logical. If TRUE (default) a plot of the acf is created
See Also
AnaCoDa documentation built on Jan. 8, 2021, 2:37 a.m.
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Description Usage Arguments See Also
View source: R/plotMCMCAlgorithmObject.R
Description
The function calculates and by defaults plots the acf and estimates the autocorrelation in the trace.
Usage
1 |
Arguments
mcmc |
object of class MCMC |
type |
"LogPosterior" or "LogLikelihood", defaults to "LogPosterior" |
samples |
number of samples at the end of the trace used to calculate the acf |
lag.max |
Maximum amount of lag to calculate acf. Default is 10*log10(N), where N i the number of observations. |
plot |
logical. If TRUE (default) a plot of the acf is created |
See Also
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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