cumulative_distribution_function {adoptr} | R Documentation |
Cumulative distribution function
Description
cumulative_distribution_function
evaluates the cumulative distribution
function of a specific distribution dist
at a point x
.
Usage
cumulative_distribution_function(dist, x, n, theta, ...)
## S4 method for signature 'Binomial,numeric,numeric,numeric'
cumulative_distribution_function(dist, x, n, theta, ...)
## S4 method for signature 'ChiSquared,numeric,numeric,numeric'
cumulative_distribution_function(dist, x, n, theta, ...)
## S4 method for signature 'NestedModels,numeric,numeric,numeric'
cumulative_distribution_function(dist, x, n, theta, ...)
## S4 method for signature 'Normal,numeric,numeric,numeric'
cumulative_distribution_function(dist, x, n, theta, ...)
## S4 method for signature 'Student,numeric,numeric,numeric'
cumulative_distribution_function(dist, x, n, theta, ...)
## S4 method for signature 'Survival,numeric,numeric,numeric'
cumulative_distribution_function(dist, x, n, theta, ...)
Arguments
dist |
a univariate |
x |
outcome |
n |
sample size |
theta |
distribution parameter |
... |
further optional arguments |
Details
If the distribution is Binomial
,
theta denotes the rate difference between
intervention and control group.
Then, the mean is assumed to be
√ n theta.
If the distribution is Normal
, then
the mean is assumed to be
√ n theta.
Value
value of the cumulative distribution function at point x
.
Examples
cumulative_distribution_function(Binomial(.1, TRUE), 1, 50, .3)
cumulative_distribution_function(Pearson2xK(3), 1, 30, get_tau_Pearson2xK(c(0.3,0.4,0.7,0.2)))
cumulative_distribution_function(ZSquared(TRUE), 1, 35, get_tau_ZSquared(0.4, 1))
cumulative_distribution_function(ANOVA(3), 1, 30, get_tau_ANOVA(c(0.3, 0.4, 0.7, 0.2)))
cumulative_distribution_function(Normal(), 1, 50, .3)
cumulative_distribution_function(Student(two_armed = FALSE), .75, 50, .9)
cumulative_distribution_function(Survival(0.6,TRUE),0.75,50,0.9)
[Package adoptr version 1.1.1 Index]