call.flm: Main function
In khelmsmith/flm_NE_WNV: Functional Linear Modeling For Vector-borne Disease

call.flm

R Documentation

Main function

Description

Main function

Usage

call.flm(
  pop,
  cases,
  weather,
  spi,
  spei,
  target.date = "2018-02-01",
  start.year = 2002,
  in.seed = NULL,
  lag.lengths = c(12, 18, 24, 30, 36),
  fillzeros = FALSE,
  nsim = 0,
  predict_from = "best"
)

Arguments

`pop`	County populations, a data frame with 5 variables County , fips (5 characters), year , pop100K , density .
`cases`	data on annual numbers of human cases in each county. A data.frame with 3 variables, County , year , and cases .
`weather`	monthly temperature and precipitation data for for each county. A data.frame with County , fips (5 characters), year , month (integer), tmean , and ppt .
`spi`	monthly values of the Standardized Precipitation Index for each county. County , fips (5 characters), year , month (integer), spi .
`spei`	monthly values of the Standardized Precipitation and Evapotranspiration Index for each county. County , fips (5 characters), year , month (integer), spei .
`target.date`	The last date to include for calculation of lags, a character string with ISO XXX format (yyyy-mm-dd).
`start.year`	The first year to include in the training data. Should be coercible to integer.
`in.seed`	If not NULL, the starting number for the random number generator. This makes the results repeatable. If NULL, treats cases as actual data
`lag.lengths`	the number of months to go backwards when creating lag matrices. Numeric vector.
`fillzeros`	Logical. If true, add zero predictions for counties that never had any cases.
`nsim`	Integer. Number of samples to draw from posterior distribution. Defaults to zero, which has the expected value of cases in predcases.