bss.ci.nbPearson: Bayesian sample size using ACC or ALC criterion for the...

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

Description

Bayesian sample size using ACC or ALC criterion for the negative binomial/Pearson Type VI model

Usage

bss.ci.nbPearson(crit, lam0, theta0, phi, w, rho, len = NULL,
  len.max = NULL, R = 1000, n0 = 1)

Arguments

crit	A characther string specifying the criterion. Criteria: "ACC" and "ALC".
lam0	A positive real number representing a shape parameter of the prior distribution.
theta0	A positive real number representing a shape parameter of the prior distribution.
phi	A positive real number representing a scale parameter of the prior distribution.
w	A positive real number representing the aliquot volume.
rho	A number in (0, 1). The probability of the credible interval is equal or greater than $1-rho$ depending on the criterion used.
len	A positive real number representing the length of the credible intervals in the ACC criterion.
len.max	A positive real number representing the maximum length of the credible intervals in the ALC criterion.
R	Number of replicates used in the simulation. Default is 1000.
n0	A positive integer representing the initial sample size in which the function will check the criterion. Default is 1.

Value

An integer representing the sample size.

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