layer_naomit: Omit 'NA's from predictions or other columns

In cmu-delphi/epipredict: Basic epidemiology forecasting methods

Omit NAs from predictions or other columns

Description

Omit NAs from predictions or other columns

Usage

layer_naomit(frosting, ..., id = rand_id("naomit"))

Arguments

frosting	a frosting postprocessor
...	<tidy-select> One or more unquoted expressions separated by commas. Variable names can be used as if they were positions in the data frame, so expressions like x:y can be used to select a range of variables. Typical usage is .pred to remove any rows with NA predictions.
id	a random id string

Value

an updated frosting postprocessor

Examples

jhu <- covid_case_death_rates %>%
  filter(time_value > "2021-11-01", geo_value %in% c("ak", "ca", "ny"))

r <- epi_recipe(jhu) %>%
  step_epi_lag(death_rate, lag = c(0, 7, 14)) %>%
  step_epi_ahead(death_rate, ahead = 7)

wf <- epi_workflow(r, linear_reg()) %>% fit(jhu)

f <- frosting() %>%
  layer_predict() %>%
  layer_naomit(.pred)

wf1 <- wf %>% add_frosting(f)

p <- forecast(wf1)
p

cmu-delphi/epipredict documentation built on March 5, 2025, 12:17 p.m.