log_normal_lag: #' This function generates (shifted) discrete gamma weights...

In jbracher/hhh4addon: Extensions to endemic-epidemic timeseries modeling from package surveillance

#' This function generates (shifted) discrete gamma weights which are subsequently used inside of get_weighted_lags. To be passed #' to hhh4_lag or profile_par_lag as the control$funct_lag argument. #' @param par_lag a parameter vector of length 2 to steer the lag structure, here log(shape) and log(rate), #' where shape and rate are the parameters of the discrete gamma distribution as implemented in the extraDistr package. #' @param min_lag smallest lag to include; the support of the Poisson form starts only at min_lag. Defaults to 1. #' @param max_lag highest lag to include; higher lags are cut off and he remaining weights standardized. Defaults to 5. #' @author Maria Dunbar, Johannes Bracher #' @export This function generates discretized log-normal weights which are subsequently used inside of get_weighted_lags. To be passed to hhh4_lag or profile_par_lag as the control$funct_lag argument.

Description

#' This function generates (shifted) discrete gamma weights which are subsequently used inside of get_weighted_lags. To be passed #' to hhh4_lag or profile_par_lag as the control$funct_lag argument. #' @param par_lag a parameter vector of length 2 to steer the lag structure, here log(shape) and log(rate), #' where shape and rate are the parameters of the discrete gamma distribution as implemented in the extraDistr package. #' @param min_lag smallest lag to include; the support of the Poisson form starts only at min_lag. Defaults to 1. #' @param max_lag highest lag to include; higher lags are cut off and he remaining weights standardized. Defaults to 5. #' @author Maria Dunbar, Johannes Bracher #' @export This function generates discretized log-normal weights which are subsequently used inside of get_weighted_lags. To be passed to hhh4_lag or profile_par_lag as the control$funct_lag argument.

Usage

log_normal_lag(par_lag, min_lag, max_lag)

Arguments

par_lag	a parameter vector of length 2 to steer the lag structure, here meanlog and log(sdlog), where meanlog and sdlog are the parameters of the log-normal distribution.
min_lag	smallest lag to include; the support of the Poisson form starts only at min_lag. Defaults to 1.
max_lag	highest lag to include; higher lags are cut off and he remaining weights standardized. Defaults to 5.

Author(s)

Maria Dunbar, Johannes Bracher

jbracher/hhh4addon documentation built on Feb. 16, 2024, 1:45 a.m.