pdf.ChiSquare {distributions3} R Documentation

Evaluate the probability mass function of a chi square distribution

Description

Evaluate the probability mass function of a chi square distribution

Usage

## S3 method for class 'ChiSquare'
pdf(d, x, drop = TRUE, elementwise = NULL, ...)

## S3 method for class 'ChiSquare'
log_pdf(d, x, drop = TRUE, elementwise = NULL, ...)


Arguments

 d A ChiSquare object created by a call to ChiSquare(). x A vector of elements whose probabilities you would like to determine given the distribution d. drop logical. Should the result be simplified to a vector if possible? elementwise logical. Should each distribution in d be evaluated at all elements of x (elementwise = FALSE, yielding a matrix)? Or, if d and x have the same length, should the evaluation be done element by element (elementwise = TRUE, yielding a vector)? The default of NULL means that elementwise = TRUE is used if the lengths match and otherwise elementwise = FALSE is used. ... Arguments to be passed to dchisq. Unevaluated arguments will generate a warning to catch mispellings or other possible errors.

Value

In case of a single distribution object, either a numeric vector of length probs (if drop = TRUE, default) or a matrix with length(x) columns (if drop = FALSE). In case of a vectorized distribution object, a matrix with length(x) columns containing all possible combinations.

Examples


set.seed(27)

X <- ChiSquare(5)
X

mean(X)
variance(X)
skewness(X)
kurtosis(X)

random(X, 10)

pdf(X, 2)
log_pdf(X, 2)

cdf(X, 4)
quantile(X, 0.7)

cdf(X, quantile(X, 0.7))
quantile(X, cdf(X, 7))


[Package distributions3 version 0.2.1 Index]