system_od_general | R Documentation |
Used to calculate observation details based on
cohorts created with system_define_cohort
system_od_general(pest, cfg, estimation = TRUE, details = FALSE)
pest |
vector of parameters to be estimated |
cfg |
ubiquity system object |
estimation |
|
details |
|
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
system_define_cohort
and system_simulate_estimation_results
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