Description Usage Arguments Value References See Also Examples
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.
1 2 3 4 5 |
x |
Data. |
distr |
Distribution to fit. For |
method |
Estimation method. Either maximum likelihood ('mle') or L-moments ('lmom'). |
varcov |
Should the variance-covariance matrix of the parameters
be computed. For |
lmm |
L-moments of the data.
Can be use by speed up multiple call of FitAmax
See |
nsim |
Number of simulations used to evaluate the covariance matrix when using L-moment based estimator. |
data |
Data Values. |
lmom |
L-moments. |
para |
Parameter estimates. |
varcov |
Covariance matrix of the parameter |
llik |
Value of the log-likelihood |
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.
predict.amax
, gofTest
,
plot.amax
.
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')
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