Pmetrics Run Cycle InformationSource:
This contains the output of makeCycle after a run, which generates information suitable for analysis and plotting of cycle information. Each field corresponds to a column in the complete data frame.
To manipulate the entire data frame,
data field, e.g.
final <- run1$cycle$data %>% slice_tail(n=1). If
you are unfamiliar with the
%>% pipe function, please type
into the R console and look online for instructions/tutorials in tidyverse, a
powerful approach to data manipulation upon which Pmetrics is built.
Vector of names of the random parameters
Vector cycle numbers, which may start at numbers greater than 1 if a non-uniform prior was specified for the run (NPAG only)
Matrix of cycle number and -2*Log-likelihood at each cycle
A matrix of cycle number and gamma or lambda at each cycle
A matrix of cycle number and the mean of each random parameter at each cycle, normalized to initial mean
A matrix of cycle number and the standard deviation of each random parameter at each cycle, normalized to initial standard deviation
A matrix of cycle number and the median of each random parameter at each cycle, normalized to initial median
A matrix of cycle number and Akaike Information Criterion at each cycle
A matrix of cycle number and Bayesian (Schwartz) Information Criterion at each cycle
A data frame combining all the above fields as its columns
Create new object populated with cycle information
The parsed output from makeCycle.
Arguments passed to plot.PMcycle