amomoStan: A bayesian version of the A-MOMO algorithm

In thl-mjv/momoStan: Bayesian analysis for the European Euromomo project using Stan

Description

Fits a Serfling -type model to a mortality time series by omiting summer and winter seasons from the estimation, and making predictions for the whole time span of the data. This version does not include delay adjustments

Usage

amomoStan(data, spring = 16:25, autumn = 31:47, datevar = "date",
  mortvar = "n", popvar = NA, byvar = NA, iter = 2000,
  penalties = NULL, data.only = FALSE)

Arguments

data	a data frame with all necessary variables
spring	numbers of the weeks defining Spring (use 1:53 to use all weeks)
autumn	numbers of the weeks defining Autumn (use 1:53 to use all weeks)
datevar	name of the variable containing the date of the observation (preferrably the date of the Monday)
mortvar	name of the variable containing the number of deaths
popvar	(optionally) the name of the variable containing the population denominator
byvar	(optionally) the name of the variable by which groups the analysis is done
iter	number of iterations
penalties	control the shrinkage between
data.only	if TRUE just collect all the data together and don't fit

Value

stan fit object

thl-mjv/momoStan documentation built on May 3, 2019, 2:57 p.m.