# anova.bvpot: Anova Tables: Bivariate Case In POT: Generalized Pareto Distribution and Peaks Over Threshold

## Description

Computes analysis of deviance for “bvpot” object

## Usage

 ```1 2``` ```## S3 method for class 'bvpot' anova(object, object2, ..., half = FALSE) ```

## Arguments

 `object, object2` Two objects of class “bvpot”, most often return of the `fitbvgpd` function. `...` Other options to be passed to the `anova` function. `half` Logical. For some non-regular testing problems the deviance difference is known to be one half of a chi-squared random variable. Set half to `TRUE` in these cases.

## Value

This function returns an object of class anova. These objects represent analysis-of-deviance tables.

## Warning

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

In some cases the asymptotic distribution is known to be one half of a chi-squared; you can set `half = TRUE` in these cases.

## Author(s)

Mathieu Ribatet (Alec Stephenson for the “Warning” case)

`anova`, `anova.uvpot`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10``` ```x <- rgpd(1000, 0, 1, -0.25) y <- rgpd(1000, 2, 0.5, 0) M0 <- fitbvgpd(cbind(x,y), c(0, 2)) M1 <- fitbvgpd(cbind(x,y), c(0,2), model = "alog") anova(M0, M1) ##Non regular case M0 <- fitbvgpd(cbind(x,y), c(0, 2)) M1 <- fitbvgpd(cbind(x,y), c(0, 2), alpha = 1) anova(M0, M1, half = TRUE) ```

### Example output

```Analysis of Variance Table

MDf Deviance Df  Chisq Pr[>Chisq]
M0   5   2347.2
M1   7   2228.8  2 118.46 1.8915e-26
Analysis of Variance Table

MDf Deviance Df   Chisq Pr[>Chisq]
M1   4   2234.4
M0   5   2347.2  1 -225.67          1
```

POT documentation built on May 2, 2019, 7:30 a.m.