geom_c_opt {hytest} | R Documentation |
Critical Value Given a Nominal Error Type I Associated with a Geometric Distribution
Description
geom_c_opt
is used to obtain a critical value to achieve a nominal error type I when we use a random sample from a Geometric distribution.
Usage
geom_c_opt(
alpha = 0.1,
n = 100,
theta0 = 0.5,
c1 = 0.001,
c2 = 0.999,
R = 15000,
delta = 0.005,
tolerance = 0.01,
max_iter = 100
)
Arguments
alpha |
numeric, represents a nominal error type I. Default value is 0.1. |
n |
numeric, represents the size of the sample. Default value is 100. |
theta0 |
numeric, represents the probability parameter under the null hypothesis of a sample from a Geometric distribution. Default value is 0.5. |
c1 |
numeric, represents a lower bound to the critical value. Default value is 1e-03. |
c2 |
numeric, represents an upper bound to the critical value. Default value is 0.99. |
R |
numeric, represents the number of replicates. Default value is 15000. |
delta |
numeric, represents a precision parameter. Default value is 0.005. |
tolerance |
numeric, represents a relative precision with respect a given alpha. Default value is 0.01. |
max_iter |
integer, represents the maximum number of iterations. Default value is 100. |
Value
A list with number of replicates, sample size, nominal error type I, and empirical critical value obtained associated with a likelihood ratio statistic.
Author(s)
Carlos Alberto Cardozo Delgado <cardozorpackages@gmail.com>.
References
Casella, G. and Berger, R. (2003). Statistical Inference, Second Edition. Duxbury Press.
Hogg, R., McKean, J., and Craig, A. (2019) Introduction to Mathematical Statistic. Eighth edition. Pearson.
Examples
# Critical value when we use a random sample of size 80 from a Geometric distribution
# given a nominal error type I equals to 0.1 and R = 10000
# to test H_0: theta = 0.25 vs H_1: theta != 0.25
geom_c_opt(alpha=0.1,n=80,theta0=0.25,R=10000)