mixture: Modeling the Prevalence and the Force of Infection Directly...

In TeaKov/serostat: Modeling Infectious Disease Parameters Based on Serological and Social Contact Data R Package

Description

True prevalence and force of infection can be derived directly by using a two-component mixture model for the antibody activity levels. The group of infected individuals and the group of susceptible individuals form the two components with the true prevalence as age-dependent mixing probability.

Usage

mix(mixdat, mixpar, dist = "norm", ...)

Arguments

mixdat	A data frame containing grouped data, whose first column should be right boundaries of grouping intervals where the first and last intervals are open-ended; whose second column should consist of the frequencies indicating numbers of observations falling into each interval. If conditional data are available, this data frame should have k + 2 columns, where k is the number of components, whose element in row j and column i + 2 is the number of observations from the jth interval belonging to the ith component.
mixpar	A data frame containing starting values for parameters of component distributions, which are, in order, the proportions, means, and standard deviations.
dist	The distribution of components, it can be one of “norm”, “lnorm”, “gamma”, “weibull”, “binom”, “nbinom”, and “pois”
...	See mix.

Details

See page 171 of the book.

See Also

mpspline.fit, Threshold, mix

Examples

library(mixdist)
data("VZV_B19_BE_0103")
subset <- (VZV_B19_BE_0103$age<40.5)&(!is.na(VZV_B19_BE_0103$age))&
  (!is.na(VZV_B19_BE_0103$VZVmUIml))
VZV_B19_BE_0103<-VZV_B19_BE_0103[subset,]

z1<-log(VZV_B19_BE_0103$VZVmUIml[order(VZV_B19_BE_0103$age)]+1)

zmixdat <- mixgroup(z1,breaks=40)
zstartpar <- mixparam(pi=c(0.2,0.8), mu=c(2,6), sigma=c(0.5,1))
mixfit <- mix(zmixdat,zstartpar,dist="norm")
summary(mixfit)

TeaKov/serostat documentation built on May 21, 2019, 1:21 p.m.