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Last data update: 2014.03.03

R: Define a 'renouvellement' model without estimation

RenouvNoEst

R Documentation

Define a 'renouvellement' model without estimation

Description

Build a 'renouvellement' model using parameters given by the user.

Usage

RenouvNoEst(threshold,
            estimate = NULL,
            distname.y = "exponential",
            fixed.par.y = NULL,
            trans.y = NULL,
            pct.conf = c(95, 70),
            rl.prob = NULL,
            prob.max = 1 - 1e-04,
            pred.period = NULL,
            cov = NULL,
            nb.OT = NULL,
            infer.method = NULL)

Arguments

`threshold`	The threshold.
`estimate`	Numeric named vector containing the estimates for the parameters. It must be compatible with the distribution chosen, and must contain in first position an element named `"lambda"` representing an estimated event rate in events by year.
`distname.y`	Character giving the name of the distribution.
`fixed.par.y`	Numeric named vector containing values for vectors which are considered as fixed (and not estimated).
`trans.y`	Transformation as in `Renouv`. Used only when `distname.y` is equal to `"exponential"`.
`pct.conf`	Vector of percents for confidence limits.
`rl.prob`	Probability used in the return level computations. These values are used for instance in return level plots produced with the `plot.Renouv` method. When `NULL` a default vector is used.
`prob.max`	Maximal probability for which computations are done.
`pred.period`	Vector of periods for which predicted return levels will be computed.
`cov`	Covariance matrix for the provided estimated parameters. Must have rownames and colnames in accordance with those of `estimate`. This covariance matrix is used to build confidence limits on parameters and on return levels using the delta method.
`nb.OT`	Number of data over the threshold used for estimation. This will be used only when `distname.y` is equal to `"exponential"`.
`infer.method`	Inference method. Will normally be the delta method.

Details

This function is used for plotting or comparing models with known parameter estimates but with no data available.

The parameters estimates should be accompanied with a covariance matrix assuming an approximately normal joint distribution of these. This matrix is usually obtained by computing the numerical derivatives of the log-likelihood at the second order at the estimates. This covariance is used to compute approximate confidence limits for the return levels of the unknown true distribution that was estimated.

Value

An object of class "Renouv" representing a 'renouvellement' model similar to those built with Renouv. This is mainly a list. Note however that some list elements found in Renouv objects built by Renouv can not be found here. For instance, the returned objects embeds no goodness-of-fit results since the object is created without making use of any data.

Author(s)

Yves Deville

Examples

##======================================================================
## Example from S. Coles' book, page 86 'rainfall data'
##======================================================================
estimate <- c(lambda = 152/48, scale = 7.44, shape = 0.184)          
cov <- matrix(c(4.9e-7,  0.0000,  0.0000,
                0.0000,  0.9180, -0.0655,
                0.0000, -0.0655,  0.0102),
              nrow = 3)
colnames(cov) <- rownames(cov) <- names(estimate)
renNE <- RenouvNoEst(threshold = 30, distname.y = "gpd",
                     pct.conf = c(95, 70),
                     estimate = estimate,
                     nb.OT = 152, cov = cov)
summary(renNE)
plot(renNE, main = "Daily rainfall data SW England", ylim = c(0, 400) )

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.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
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/RenouvNoEst.Rd_%03d_medium.png", width=480, height=480)
> ### Name: RenouvNoEst
> ### Title: Define a 'renouvellement' model without estimation
> ### Aliases: RenouvNoEst
> 
> ### ** Examples
> 
> ##======================================================================
> ## Example from S. Coles' book, page 86 'rainfall data'
> ##======================================================================
> estimate <- c(lambda = 152/48, scale = 7.44, shape = 0.184)          
> cov <- matrix(c(4.9e-7,  0.0000,  0.0000,
+                 0.0000,  0.9180, -0.0655,
+                 0.0000, -0.0655,  0.0102),
+               nrow = 3)
> colnames(cov) <- rownames(cov) <- names(estimate)
> renNE <- RenouvNoEst(threshold = 30, distname.y = "gpd",
+                      pct.conf = c(95, 70),
+                      estimate = estimate,
+                      nb.OT = 152, cov = cov)
> summary(renNE)
o Estimated rate 'lambda' for Poisson process (events):  3.17 evt/year.

o Distribution for exceedances y: "gpd", with 2 par. "scale", "shape" 

o No transformation applied

o Coefficients

       Estimate Std. Error     t value
lambda 3.166667  0.0007000 4523.809524
scale  7.440000  0.9581232    7.765181
shape  0.184000  0.1009950    1.821871

Degrees of freedom: 3 (param.) and 152 (obs)

o Inference method used for return levels
"Delta method"

o Return levels

   period quant L.95 U.95 L.70 U.70
31     10    66   56   76   61   71
34     20    76   60   92   68   85
36     50    92   64  120   78  107
39    100   106   66  147   85  128
42    200   122   65  179   92  152
43    300   132   63  201   96  169
45    400   140   62  218   99  182
46    500   146   60  233  101  192
47    600   152   58  245  102  201
49    700   156   57  256  104  209
51    800   161   55  266  105  216
52    900   164   54  275  106  223
53   1000   168   52  283  107  229


o no 'MAX' historical data

o no 'OTS' historical data

o Kolmogorov-Smirnov test
NULL

> plot(renNE, main = "Daily rainfall data SW England", ylim = c(0, 400) )
> 
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>