plot_diagnostics: Plot MCMC diagnostics.
In kieranrcampbell/ouija: Interpretable marker-based single-cell pseudotime using Bayesian parametric models
Description
Usage
Arguments
Details
Value
Examples
Description
Plot MCMC diagnostics (traceplot and autocorrelation) of the log-posterior probability
for a ouija_fit object.
Usage
1
plot_diagnostics(oui, arrange = c("vertical", "horizontal"))
Arguments
oui
A ouija_fit object
arrange
How to arrange the plots. If "vertical", traceplot and autocorrelation are
arranged in one column, while if "horizontal" traceplot and autocorrelation are arranged
in one row.
Details
Further assessment of convergence can be done using rstan functions on the
underlying STAN object (accessed through oui$fit).
Value
A ggplot2 object
Examples
1
2
kieranrcampbell/ouija documentation built on Dec. 2, 2019, 12:44 p.m.
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Description Usage Arguments Details Value Examples
Description
Plot MCMC diagnostics (traceplot and autocorrelation) of the log-posterior probability
for a ouija_fit object.
Usage
1 | plot_diagnostics(oui, arrange = c("vertical", "horizontal"))
|
Arguments
oui |
A |
arrange |
How to arrange the plots. If "vertical", traceplot and autocorrelation are arranged in one column, while if "horizontal" traceplot and autocorrelation are arranged in one row. |
Details
Further assessment of convergence can be done using rstan functions on the
underlying STAN object (accessed through oui$fit).
Value
A ggplot2 object
Examples
1 2 |
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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