In stephaneguerrier/CPreval: TO DO

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-"
)
library(CPreval)

CPrval Overview

This R package provides an implementation of the estimators discussed in Accurate Prevalence Estimation for Emerging or Rare Infectious Diseases by Stéphane Guerrier, Christoph Kuzmics and Maria-Pia Victoria-Feser (submitted manuscript available upon request). The pacakge can be installed from GitHub as follows:

# Install devtools
install.packages("devtools")

# Install the package from GitHub
devtools::install_github("stephaneguerrier/CPreval")

Example

Consider the following data:

seed = 18
n    = 1500
p0   = 3/100
pi0  = 1/100
(X = sim_Rs(p = p0, pi0 = pi0, n = n, seed = seed))

Estimators:

survey_sample(X$R, X$n)
moment_estimator(R0 = X$R0, R = X$R, pi0 = X$pi0, n = X$n)
mle(R0 = X$R0, R = X$R, pi0 = X$pi0, n = X$n)

With measurement error:

alpha0 = 1/100
alpha  = 1/100
beta0  = 6/100
beta   = 6/100
(X = sim_Rs(p = p0, pi0 = pi0, n = n, seed = seed,
           alpha = alpha, alpha0 = alpha0, 
           beta = beta, beta0 = beta0))

Without taking into account measurement error:

survey_sample(X$R, X$n)
moment_estimator(R0 = X$R0, R = X$R, pi0 = X$pi0, n = X$n)
mle(R0 = X$R0, R = X$R, pi0 = X$pi0, n = X$n)

Taking into account measurement error:

survey_sample(X$R, X$n, alpha = alpha, beta = beta)
moment_estimator(R0 = X$R0, R = X$R, pi0 = X$pi0, n = X$n, 
                 alpha = alpha, alpha0 = alpha0, 
                 beta = beta, beta0 = beta0)
mle(R0 = X$R0, R = X$R, pi0 = X$pi0, n = X$n, 
                 alpha = alpha, alpha0 = alpha0, 
                 beta = beta, beta0 = beta0)

License

The license this source code is released under is the GNU AFFERO GENERAL PUBLIC LICENSE (AGPL) v3.0. Please see the LICENSE file for full text. Otherwise, please consult TLDR Legal or GNU which will provide a synopsis of the restrictions placed upon the code.

stephaneguerrier/CPreval documentation built on June 6, 2020, 2:28 a.m.