fit_hts: Fit a hierarchical time series model

In njtierney/yahtsee: Yet Another Hierachical Time Series Extension and Expansion

Description

Fit a hierarchical time series model

Usage

fit_hts(
  formula,
  .data,
  special_index,
  family,
  verbose = TRUE,
  keep_data = TRUE,
  ...
)

Arguments

formula	formula must contain fixed effect terms and hts()
.data	a tsibble
special_index	The variable that represents time in your data
family	character.
verbose	default TRUE, whether to display message
keep_data	attach the data used to fit the model to the final model object?
...	list of options to pass to inlabru::bru, see ?inlabru::bru to see these options.

Value

inlabru model

How to allow weighting of observations?

To weight your observations, say when using empirical logit, you must provide a vector of variances, for each observation, which represents the uncertainty of measurement. You can do this, provided the family = "gaussian", add the argument, scale = vec, to fit_hts, where vec is a vector of variances for each observation.

Examples

## Not run: 
m <- fit_hts(
#inputs are  the levels of hierarchy, in order of decreasing size
formula = pr ~ avg_lower_age + hts(who_subregion, country),
.data = malaria_africa_ts,
family = "gaussian",
special_index = month_num
)

## End(Not run)

njtierney/yahtsee documentation built on Feb. 5, 2022, 8:25 p.m.