| system_od_general {ubiquity} | R Documentation |
General Observation Details Function
Description
Used to calculate observation details based on
cohorts created with system_define_cohort
Usage
system_od_general(pest, cfg, estimation = TRUE, details = FALSE)
Arguments
pest |
vector of parameters to be estimated |
cfg |
ubiquity system object |
estimation |
|
details |
|
Value
If estimation is TRUE then the output is a matrix of observation details of the format:
od$pred = [TIME, OBS, PRED, VAR, OUTPUT, COHORT]
The values are the observed (OBS) data, predicted
values (PRED) and variance (VAR) at the given TIME. The columns OUTPUT and
COHORT can be used for sorting. These should be unique numbers.
When estimation is FALSE we output od$pred is a data frame with the
following headings:
od$pred = [TIME, OBS, PRED, VAR, SMOOTH, OUTPUT, COHORT]
The TIME, OBS, PRED and VAR are the same as those listed above. The SMOOTH
variable is FALSE for rows that correspond to records in the dataset and
TRUE when the PRED represents the smooth predictions. The OUTPUT and COHORT
columns here are text values used when defining the cohorts.
Also the od$all list item is created with all of the simulation information
stored for each cohort:
od$all = [ts.time, ts.ts1, ... ts.tsn, pred, name, cohort]
-
tstime- timescale of the system -
ts.ts1, ... ts.tsn- timescales defined in the system -
pred- smooth prediction -
name- state or output name corresponding to the prediction -
cohort- name of the cohort for these predictions
Lastly the field isgood will be set to FALSE if any problems are encountered, and TRUE if everything worked.
od$isgood = TRUE
See Also
system_define_cohort and system_simulate_estimation_results