bss.dt.PoiDP: Bayesian sample size in a decision-theoretic approach for the...

In eliardocosta/ssdet: Sample size determination in frequentist and Bayesian approaches

Description

Bayesian sample size in a decision-theoretic approach for the Poisson/Dirichlet process.

Usage

bss.dt.PoiDP(lam0, theta0, alpha, w, c, nmax = 100, nrep = 10,
  R = 100, plot = TRUE, ...)

Arguments

lam0	A positive real number representing a hyperparameter of the $F_0$ base distribution.
theta0	A positive real number representing a hyperparameter of the $F_0$ base distribution. We consider $F_0$ as the gamma distribution with mean $lam_0$ and shape parameter $theta_0$.
alpha	Shape parameter of the Dirichlet process.
w	A positive real number representing the aliquot volume.
c	A positive real number representing the cost of colect one aliquot.
nmax	A positive integer representing the maximum number for compute the Bayes risk. Default is 100.
nrep	A positive integer representing the number of samples taken for each $n$.
R	Number of replicates used in the simulation. Default is 100.
plot	Boolean. If TRUE (default) it plot the estimated Bayes risks and the fitted curve.
...	Currently ignored.

Value

An integer representing the sample size.

eliardocosta/ssdet documentation built on Dec. 14, 2021, 6:27 a.m.