anova.evd {evd} | R Documentation

## Compare Nested EVD Objects

### Description

Compute an analysis of deviance table for two or more nested evd objects.

### Usage

    ## S3 method for class 'evd':
    anova(object, object2, ...)

### Arguments

`object` | An object of class `"evd"`.
`object2` | An object of class `"evd"` that represents a model nested within `object`.
`...` | Further successively nested objects.

### Value

An object of class `c("anova", "data.frame")`, with one row for each model, and the following five columns

`M.Df` | The number of parameters.
`Deviance` | The deviance.
`Df` | The number of parameters of the model in the previous row minus the number of parameters.
`Chisq` | The deviance minus the deviance of the model in the previous row.
`Pr(>chisq)` | The p-value calculated by comparing the quantile `Chisq` with a chi-squared distribution on `Df` degrees of freedom.

### Warning

Circumstances may arise such that the asymptotic distribution of the test statistic is not chi-squared. In particular, this occurs when the nested model is constrained at the edge of the parameter space. It is up to the user recognize this, and to interpret the output correctly.

### See Also

`fbvevd`, `fextreme`, `fgev`, `forder`

### Examples

    uvdata <- rgev(100, loc = 0.13, scale = 1.1, shape = 0.2)
    trend <- (-49:50)/100
    M1 <- fgev(uvdata, nsloc = trend)
    M2 <- fgev(uvdata)
    M3 <- fgev(uvdata, shape = 0)
    anova(M1, M2, M3)

    bvdata <- rbvevd(100, dep = 0.75, model = "log")
    M1 <- fbvevd(bvdata, model = "log")
    M2 <- fbvevd(bvdata, model = "log", dep = 0.75)
    anova(M1, M2)

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