FitAmax: At-site frequency analysis using annual maxima

Description Usage Arguments Value References See Also Examples

Description

Return the fitting of a distribution of annual maxima. Both maximum likelihood and L-moments method are available. If the maximum likelihood method fails, the L-moments is returned and a warning message is issued. The function FitAmax.auto select automatically the best distribution according to the AIC criteria and return the fitted object.

Usage

1
2
3
4
5
FitAmax(x, distr = "gev", method = "lmom", varcov = TRUE,
  lmm = NULL, nsim = 1000)

FitAmax.auto(x, distr = c("gev", "gno", "pe3", "glo"), ...,
  tol.gev = 0)

Arguments

x

Data.

distr

Distribution to fit. For FitAmax.auto it is a list of candidate distributions. See vec2par for the list of available distribution.

method

Estimation method. Either maximum likelihood ('mle') or L-moments ('lmom').

varcov

Should the variance-covariance matrix of the parameters be computed. For mle the covariance matrix is derived from the hessian matrix. For L-moments, non-parametric bootstrap is used.

lmm

L-moments of the data. Can be use by speed up multiple call of FitAmax See lmoms.

nsim

Number of simulations used to evaluate the covariance matrix when using L-moment based estimator.

Value

data

Data Values.

lmom

L-moments.

para

Parameter estimates.

varcov

Covariance matrix of the parameter

llik

Value of the log-likelihood

References

Coles, S. (2001). An introduction to statistical modeling of extreme values. Springer Verlag.

Hosking, J. R. M., & Wallis, J. R. (1997). Regional frequency analysis: an approach based on L-moments. Cambridge Univ Pr.

See Also

predict.amax, gofTest, plot.amax .

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
## Extract an time series of annual maxima
x <- ExtractAmax(flow~date, flowStJohn)$flow

## Fitting of GEV distribution using L-moments

fit <- FitAmax(x,'gev')
print(fit)
coef(fit)
AIC(fit)
fit$lmom

## The evaluation of the covariance matrix can be avoided for speeding up
## the estimation
fit <- FitAmax(x,'gev', varcov = FALSE)

## Using Maximum likelihood
fit <- FitAmax(x,'gev', method ='mle')
print(fit)
vcov(fit)

## Standard deviation of the parameter
sqrt(diag(vcov(fit)))

## Chose the best distribution according to AIC
FitAmax.auto(x, distr = c('gev','glo','gno','pe3'), method = 'mle')

martindurocher/floodStat documentation built on May 31, 2019, 12:42 a.m.