SUMMER (version 0.3.0)

getSmoothed: Function to obtain projected estimates from INLA for each time and region.

Description

Function to obtain projected estimates from INLA for each time and region.

Usage

getSmoothed(inla_mod, year_range = c(1985, 2019),
  year_label = c("85-89", "90-94", "95-99", "00-04", "05-09", "10-14",
  "15-19"), Amat = NULL, nsim = 1000, weight.strata = NULL,
  verbose = FALSE, mc = 0, include_time_unstruct = FALSE, ...)

Arguments

inla_mod

output from fitINLA

year_range

range corresponding to year label

year_label

vector of year string vector

Amat

adjacency matrix

nsim

number of simulations

weight.strata

a data frame with three columns, years, region, and proportion of each strata for the corresponding time period and region.

verbose

logical indicator whether to print progress messages from inla.posterior.sample.

mc

number of monte carlo draws to approximate the marginal prevalence/hazards for binomial model. If mc = 0, analytical approximation is used. The analytical approximation is invalid for hazard modeling with more than one age groups.

include_time_unstruct

logical indicator whether to include the temporal unstructured effects (i.e., shocks) in the smoothed estimates.

...

additional configurations passed to inla.posterior.sample.

Value

Results from RW2 model fit, including projection.

See Also

plot.SUMMERproj

Examples

# NOT RUN {
years <- levels(DemoData[[1]]$time)

# obtain direct estimates
data <- getDirectList(births = DemoData, 
years = years,  
regionVar = "region", timeVar = "time", 
clusterVar = "~clustid+id", 
ageVar = "age", weightsVar = "weights", 
geo.recode = NULL)
# obtain direct estimates
data_multi <- getDirectList(births = DemoData, years = years,
  regionVar = "region",  timeVar = "time", clusterVar = "~clustid+id",
  ageVar = "age", weightsVar = "weights", geo.recode = NULL)
data <- aggregateSurvey(data_multi)

#  national model
years.all <- c(years, "15-19")
fit1 <- fitINLA(data = data, geo = NULL, Amat = NULL, 
  year_label = years.all, year_range = c(1985, 2019), 
  rw = 2, is.yearly=FALSE, m = 5)
out1 <- getSmoothed(fit1)
plot(out1, is.subnational=FALSE)

#  subnational model
fit2 <- fitINLA(data = data, geo = geo, Amat = mat, 
  year_label = years.all, year_range = c(1985, 2019), 
  rw = 2, is.yearly=TRUE, m = 5, type.st = 4)
out2 <- getSmoothed(fit2, Amat = mat)
plot(out2, is.yearly=TRUE, is.subnational=TRUE)


# }
# NOT RUN {
# }