predict.fit_pansim: make forecasts from sim

In bbolker/McMasterPandemic: Pandemic Model

make forecasts from sim

Description

make forecasts from sim

Usage

## S3 method for class 'fit_pansim'
predict(
  object,
  end_date = NULL,
  stoch = NULL,
  stoch_start = NULL,
  keep_vars = c("H", "ICU", "death", "hosp", "incidence", "report", "cumRep",
    "newTests/1000"),
  ensemble = FALSE,
  new_params = NULL,
  Sigma = NULL,
  scale_Sigma = 1,
  ...
)

## S3 method for class 'fit_pansim'
plot(
  x,
  predict_args = NULL,
  data = NULL,
  break_dates = NULL,
  dlspace = 1,
  limspace = 10,
  add_tests = FALSE,
  add_ICU_cap = FALSE,
  mult_var = NULL,
  directlabels = TRUE,
  log = TRUE,
  log_lwr = 1,
  ...
)

Arguments

object	a fitted object
end_date	ending date for sim
stoch	stochasticity
stoch_start	stoch starting date
keep_vars	...
ensemble	run ensemble?
new_params	parameters to update in base parameters (e.g. adding stochastic parameters)
Sigma	covariance matrix
scale_Sigma	inflate/deflate covariance matrix
...	extra args (passed to forecast_ensemble)
x	a calibrated object (result from calibrate) or a prediction (from predict.fit_pansim)
predict_args	additional arguments to pass to predict
data	original time series data
break_dates	breakpoints
dlspace	spacing for direct labels (not working)
limspace	extra space (in days) to add to make room for direct labels
add_tests	plot newTests/1000?
add_ICU_cap	include horizontal lines showing ICU capacity?
mult_var	variable in data set indicating multiple forecast types to compare
directlabels	use direct labels?
log	use a log10 scale for the y axis?
log_lwr	lower limit when using log scale

Examples

pp1 <- predict(ont_cal1, keep_vars="Rt")
## example of hacking params
ont_cal2 <- ont_cal1
ont_cal2$forecast_args$base_params["zeta"] <- 4
pp2 <- predict(ont_cal2, keep_vars="Rt")
## if zeta is fitted probably need to hack x$mle2@coef, e.g.
ont_cal3 <- ont_cal1
## increase beta0 (from -0.34) rather than
## mess with zeta, since phenom het isn't
## estimated in this fit
ont_cal3$mle2@fullcoef["params.log_beta0"] <- 0
pp3 <- predict(ont_cal3, keep_vars="Rt")
pp <- dplyr::bind_rows(base=pp1,zeta=pp2,beta0=pp3, .id="fit")
if (require("ggplot2")) {
   ggplot(pp,aes(date,value,colour=fit))+geom_line()
}
## Not run: 
## non-pos-def vcov ... ???
predict(ont_cal_2brks,ensemble=TRUE)

## End(Not run)

bbolker/McMasterPandemic documentation built on Aug. 25, 2024, 6:35 p.m.