# sample.size.count.poisson.onesample.exact: Sample Size - Single Sample Poisson Test In burrm/lolcat: Miscellaneous Useful Functions

## Description

Sample size calculation utilizes the exact power calculation.

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14``` ```sample.size.count.poisson.onesample.exact( lambda.null.hypothesis, lambda.alternative.hypothesis, alpha = 0.05, beta = 0.1, alternative = c("two.sided", "less", "greater"), details = TRUE, power.from.actual = F, n.initial = sample.size.count.poisson.onesample.approximate(lambda.null.hypothesis = lambda.null.hypothesis, lambda.alternative.hypothesis = lambda.alternative.hypothesis, alpha = alpha, beta = beta, alternative = alternative, details = FALSE), max.iteration = 10000 ) ```

## Arguments

 `lambda.null.hypothesis` Scalar - null hypothesis lambda parameter `lambda.alternative.hypothesis` Scalar - alternative hypothesis lambda parameter `alpha` Scalar - Type I error rate `beta` Scalar - Type II error rate `alternative` Scalar (character) - alternative hypothesis `details` Logical - Return calculation details (default) or return only sample size (details = FALSE) `power.from.actual` Logical - If true, return 1-beta, if false, calculate power using calculated sample size. `n.initial` Scalar - Integer with initial sample size guess. `max.iteration` Scalar - Maximum iterations to perform before declaring failure.

## Value

A data frame with details about the calculation or a single value with sample size (details = F).

burrm/lolcat documentation built on Nov. 22, 2021, 10:53 a.m.