excessProb.pb {BMAmevt} R Documentation

## Estimates the probability of joint excess (Frechet margins)

### Description

Double Monte-Carlo integration.

### Usage

```excessProb.pb(
post.sample,
Nmin.intern = 100,
precision = 0.05,
from = NULL,
to = NULL,
thin = 100,
displ = FALSE,
thres = rep(500, 5),
known.par = FALSE,
true.par
)
```

### Arguments

 `post.sample` The posterior sample. `Nmin.intern` The minimum number of MC iteration in the internal loop (excess probability, conditional to a parameter). `precision` The desired precision for the internal MC estimate `from` Integer or `NULL`. If `NULL`, the default value is used. Otherwise, should be greater than `post.sample\$Nbin`. Indicates the index where the averaging process should start. Default to `post.sample\$Nbin +1` `to` Integer or `NULL`. If `NULL`, the default value is used. Otherwise, must be lower than `Nsim+1`. Indicates where the averaging process should stop. Default to `post.sample\$Nsim`. `thin` Thinning interval. `displ` logical. Should a plot be produced ? `thres` A multivariate threshold `known.par` Logical `true.par` The true parameter from which the data are issued.

### Value

A list made of

whole

A vector of estimated excess probabilities, one for each element of the thinned posterior sample.

mean

the estimated threshold excess probability: mean estimate.

esterr

The estimated standard deviation of the mean estimate (where the Monte-Carlo error is neglected)

estsd

The estimated standard deviation of the posterior sample (where the Monte-Carlo error is neglected)

lowquants

The three lower 0.1 quantiles of, respectively, the conditional mean estimates and of the upper and lower bounds of the Gaussian (centered) 80 % confidence intervals around the conditional estimates.

upquants

The three upper 0.9 quantiles

true.est

the mean estimate conditional to the true parameter: a vector of size three: the mean estimate , and the latter +/- the standard deviation of the estimate

[Package BMAmevt version 1.0.4 Index]