R: Perform Hypothesis Test Of Independence

evind.test {evd} | R Documentation

## 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")

[Package evd version 2.3-3 Index]