This function creates summary statistics for Jaatha models. A summary statistic consists primarily of a function that calculates the statistic from the simulation results. Jaatha primarily supports Poisson distributed summary statistics, but can also transform summary statistics that follow a different distribution in approximately Poisson distributed statistics.
create_jaatha_stat(name, calc_func, poisson = TRUE, breaks = c(0.1, 0.5, 0.9))The summary statistic. Indented for being used with
create_jaatha_model.
The name of the summary statistic
The function that summarizes the simulation data. Must take
two arguments. The first is the simulated data, and the second are
options that can be calculated from the real data. Ignoring the second
argument in the function body should be fine in most situations. The
function must return a numeric vector if poisson = TRUE, and can
also return a numeric matrix if poisson = FALSE.
If TRUE, it is assumed that the summary statistic
values are (at least approximately) independent and Poisson distributed.
If it is set to FALSE, the statistic is transformed into an approximately
Poisson distributed array using a binning approach. See "Transformation
of non Poisson distributed statistics" for details. If any summary
statistic is only approximately Poisson distributed, Jaatha is a
composite-likelihood method.
The probabilities for the quantiles that are used for binning the data. See the section on non Poisson distributed summary statistics for details.
To transform a statistic into approximately Poisson distributed values,
we first calculate the empirical quantiles of the real data for the
probabilities given in breaks. These are used as break points for
divining the range of the statistic into disjunct intervals. We then count
who many of the values for the simulated data fall into each intervals, and
use this counts as summary statistic. The counts are multinomial
distributed, and should be close to the required Poisson distribution in
most cases.