A named vector of parameters or an object of class "Renouv".
In the first case, the names of the vector element must conform to
the exponential distribution so the vector must be of length 2 with
names "lambda" and "rate".
threshold
A threshold associated with the parameters. If object is an
object with class "Renouv", its threshold slot will be used.
w
A block duration or a vector of block durations.
distname.y
The name of the distribution for the excesses. Can be either
"exponential" or "exp". The choice has no impact on
the computations, but this name will be attached to the result as an
attribute and may affect later use.
jacobian
Logical. If TRUE the jacobian matrix of the transformation
will be computed and attached to the result as an attribute.
vcovRen
A covariance matrix for the Renouv parameters.
Value
A vector of GEV parameters if w has length 1, and a matrix if
w has length > 1. The returned objects has attributes.
Author(s)
Yves Deville
See Also
Ren2gev for the translation of Renouv parameters
corresponding to GPD excesses.
Examples
## Fit a Renouv model with exponential excesses (default)
fit <- Renouv(Garonne)
## Convert to gumbel (usable for one-year block maxima)
parGumbel <- Ren2gumbel(fit)
## Retrieve the 'Renouv' model by giving the right threshold
parRen <- gumbel2Ren(parGumbel,
threshold = 2500,
vcovGumbel = attr(parGumbel, "vcov"),
plot = TRUE)
## Build a compatible model under the assumption of one event by
## year
parRen2 <- gumbel2Ren(parGumbel,
lambda = 1.00,
vcovGumbel = attr(parGumbel, "vcov"),
plot = TRUE)
parRenNames <- c("lambda", "rate")
## Build a 'Renouv' object without estimation
myVcov <- attr(parRen, "vcov")[parRenNames, parRenNames]
fitNew <- RenouvNoEst(threshold = attr(parRen, "threshold"),
estimate = parRen,
distname.y = "exp",
cov = myVcov)
## Compare return levels
cbind(roundPred(fit$pred)[ , -2], roundPred(fitNew$pred)[ , -2])
## idem for the putative 'Renouv' with rate 1
myVcov2 <- attr(parRen2, "vcov")[parRenNames, parRenNames]
fitNew2 <- RenouvNoEst(threshold = attr(parRen2, "threshold"),
estimate = parRen2,
distname.y = "exp",
cov = myVcov2)
cbind(roundPred(fit$pred)[ , -2], roundPred(fitNew2$pred)[ , -2])
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
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Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(Renext)
Loading required package: evd
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/Renext/Ren2gumbel.Rd_%03d_medium.png", width=480, height=480)
> ### Name: Ren2gumbel
> ### Title: Translate a vector of coefficients from a Renewal-POT model with
> ### exponential excesses to a vector of Gumbel parameters
> ### Aliases: Ren2gumbel
>
> ### ** Examples
>
> ## Fit a Renouv model with exponential excesses (default)
> fit <- Renouv(Garonne)
> ## Convert to gumbel (usable for one-year block maxima)
> parGumbel <- Ren2gumbel(fit)
> ## Retrieve the 'Renouv' model by giving the right threshold
> parRen <- gumbel2Ren(parGumbel,
+ threshold = 2500,
+ vcovGumbel = attr(parGumbel, "vcov"),
+ plot = TRUE)
loc scale
loc 8719.318 2564.989
scale 2564.989 4116.247
loc scale
lambda 0.002173328 -1.849022e-03
threshold 1.000000000 0.000000e+00
rate 0.000000000 -8.615349e-07
lambda rate
lambda 3.464240e-02 1.754489e-06
rate 1.754489e-06 3.055253e-09
> ## Build a compatible model under the assumption of one event by
> ## year
> parRen2 <- gumbel2Ren(parGumbel,
+ lambda = 1.00,
+ vcovGumbel = attr(parGumbel, "vcov"),
+ plot = TRUE)
loc scale
loc 8719.318 2564.989
scale 2564.989 4116.247
loc scale
lambda 0 0.000000e+00
threshold 1 0.000000e+00
rate 0 -8.615349e-07
lambda rate
lambda 0 0.000000e+00
rate 0 3.055253e-09
> parRenNames <- c("lambda", "rate")
> ## Build a 'Renouv' object without estimation
> myVcov <- attr(parRen, "vcov")[parRenNames, parRenNames]
> fitNew <- RenouvNoEst(threshold = attr(parRen, "threshold"),
+ estimate = parRen,
+ distname.y = "exp",
+ cov = myVcov)
Warning message:
In checkDist(distname.y = distname.y) :
warning: distribution not in target list. Still EXPERIMENTAL
> ## Compare return levels
> cbind(roundPred(fit$pred)[ , -2], roundPred(fitNew$pred)[ , -2])
period L.95 U.95 L.70 U.70 period L.95 U.95 L.70 U.70
30 10 5494 6300 5684 6110 10 5501 6293 5688 6107
33 20 6160 7128 6388 6900 20 6161 7127 6389 6900
36 50 7038 8224 7318 7945 50 7033 8230 7315 7948
38 100 7701 9055 8020 8736 100 7693 9063 8016 8740
41 200 8363 9887 8722 9528 200 8352 9897 8716 9533
43 300 8750 10373 9132 9991 300 8738 10385 9126 9997
44 400 9024 10719 9424 10320 400 9012 10731 9417 10326
46 500 9237 10987 9649 10575 500 9225 11000 9643 10581
47 600 9411 11206 9834 10783 600 9398 11219 9827 10790
48 700 9558 11391 9990 10959 700 9545 11404 9983 10966
49 800 9686 11551 10125 11112 800 9672 11565 10118 11119
51 900 9798 11693 10244 11246 900 9784 11707 10237 11254
52 1000 9898 11819 10351 11367 1000 9884 11833 10343 11374
> ## idem for the putative 'Renouv' with rate 1
> myVcov2 <- attr(parRen2, "vcov")[parRenNames, parRenNames]
> fitNew2 <- RenouvNoEst(threshold = attr(parRen2, "threshold"),
+ estimate = parRen2,
+ distname.y = "exp",
+ cov = myVcov2)
Warning message:
In checkDist(distname.y = distname.y) :
warning: distribution not in target list. Still EXPERIMENTAL
> cbind(roundPred(fit$pred)[ , -2], roundPred(fitNew2$pred)[ , -2])
period L.95 U.95 L.70 U.70 period L.95 U.95 L.70 U.70
30 10 5494 6300 5684 6110 10 5608 6187 5744 6050
33 20 6160 7128 6388 6900 20 6268 7020 6445 6843
36 50 7038 8224 7318 7945 50 7140 8123 7371 7891
38 100 7701 9055 8020 8736 100 7800 8957 8072 8684
41 200 8363 9887 8722 9528 200 8459 9790 8773 9477
43 300 8750 10373 9132 9991 300 8845 10278 9183 9941
44 400 9024 10719 9424 10320 400 9119 10624 9474 10270
46 500 9237 10987 9649 10575 500 9331 10893 9699 10525
47 600 9411 11206 9834 10783 600 9505 11112 9884 10733
48 700 9558 11391 9990 10959 700 9652 11297 10039 10910
49 800 9686 11551 10125 11112 800 9779 11458 10174 11062
51 900 9798 11693 10244 11246 900 9891 11600 10293 11197
52 1000 9898 11819 10351 11367 1000 9991 11726 10400 11318
>
>
>
>
>
> dev.off()
null device
1
>