Description Usage Arguments Value Examples
View source: R/gamma_poisson_ppd.R
Title Poisson model of parameter theta, given gamma prior and the data. Sampling the posterior predictive distribution.
1 2 3 | gamma_poisson_ppd(sample_size, gamma_a1, gamma_b1, y1, gamma_a2, gamma_b2,
y2, confidence_interval = NULL, using_MCMC = FALSE,
poisson_fitting_mean = NULL)
|
sample_size |
How many samples to produce. |
gamma_a1 |
First parameter of theta1. |
gamma_b1 |
Second parameter of theta1. |
y1 |
Given data of the Possion distribution with gamma prior for the parameter theta1. |
gamma_a2 |
First parameter of theta2. |
gamma_b2 |
Second parameter of theta2. |
y2 |
Given data of the Possion distribution with gamma prior for the parameter theta2. |
confidence_interval |
Confidence interval to be calculated. |
using_MCMC |
Whether to use MCMC to sampling the posterior predictive distribution. |
poisson_fitting_mean |
Some given parameter for Poisson distribution to be tested. |
Sampling of the posterior predictive distribution.
1 2 3 4 5 6 7 8 9 10 11 12 | gamma_poisson_ppd(sample_size = 5000, gamma_a1 = 2, gamma_b1 = 1,
y1 = menchild30bach, gamma_a2 = 2, gamma_b2 = 1,
y2 = menchild30nobach, using_MCMC = FALSE)
gamma_poisson_ppd(sample_size = 5000, gamma_a1 = 2, gamma_b1 = 1,
y1 = menchild30bach, gamma_a2 = 2, gamma_b2 = 1,
y2 = menchild30nobach, using_MCMC = TRUE)
gamma_poisson_ppd(sample_size = 5000, gamma_a1 = 2, gamma_b1 = 1,
y1 = menchild30bach, gamma_a2 = 2, gamma_b2 = 1,
y2 = menchild30nobach, confidence_interval = c(0.025, 0.975),
using_MCMC = FALSE, poisson_fitting_mean = 1.4)
|
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