Details
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,
use the data
field, e.g. final <- run1$cycle$data %>% slice_tail(n=1)
. If
you are unfamiliar with the %>%
pipe function, please type help("%>%", "magrittr")
into the R console and look online for instructions/tutorials in tidyverse, a
powerful approach to data manipulation upon which Pmetrics is built.
Public fields
names
Vector of names of the random parameters
cynum
Vector cycle numbers, which may start at numbers greater than 1 if a non-uniform prior was specified for the run (NPAG only)
ll
Matrix of cycle number and -2*Log-likelihood at each cycle
gamlam
A matrix of cycle number and gamma or lambda at each cycle
mean
A matrix of cycle number and the mean of each random parameter at each cycle, normalized to initial mean
sd
A matrix of cycle number and the standard deviation of each random parameter at each cycle, normalized to initial standard deviation
median
A matrix of cycle number and the median of each random parameter at each cycle, normalized to initial median
aic
A matrix of cycle number and Akaike Information Criterion at each cycle
bic
A matrix of cycle number and Bayesian (Schwartz) Information Criterion at each cycle
data
A data frame combining all the above fields as its columns
Methods
Method new()
Create new object populated with cycle information
Usage
PM_cycle$new(cycle)
Arguments
cycle
The parsed output from makeCycle.