evind.test: Perform Hypothesis Test Of Independence

In evd: Functions for Extreme Value Distributions

Perform Hypothesis Test Of Independence

Description

Perform score and likelihood ratio tests of independence for bivariate data, assuming a logistic dependence model as the alternative.

Usage

evind.test(x, method = c("ratio", "score"), verbose = FALSE)

Arguments

x	A matrix or data frame, ordinarily with two columns, which may contain missing values.
method	The test methodology; either "ratio" for the likelihood ratio test or "score" for the score test.
verbose	If TRUE, shows estimates of the marginal parameters in addition to the dependence parameter.

Details

This simple function fits a stationary bivariate logistic model to the data and performs a hypothesis test of \code{dep} = 1 versus \code{dep} < 1 using the methodology in Tawn (1988). The null distributions for the printed test statistics are chi-squared on one df for the likelihood ratio test, and standard normal for the score test.

Value

An object of class "htest".

References

Tawn, J. A. (1988) Bivariate extreme value theory: models and estimation. Biometrika, 75, 397–415.

See Also

fbvevd, t.test

Examples

evind.test(sealevel)
evind.test(sealevel, method = "score")

evd documentation built on Sept. 21, 2024, 9:06 a.m.