Summary and print methods for "Renouv" objects

Summary method for "Renouv" objects representing 'Renouvellement' (POT) fitted models.

Usage

# S3 method for Renouv
print(x,
        digits = max(3L, getOption("digits") - 3L),
        ...)

   # S3 method for Renouv
summary(object,
        correlation = FALSE,
        symbolic.cor = FALSE,
        ...)

   # S3 method for summary.Renouv
print(x,
      coef = TRUE,
      pred = TRUE,
      probT = FALSE,
      digits = max(3, getOption("digits") - 3),
      symbolic.cor = x$symbolic.cor,
      signif.stars = getOption("show.signif.stars"),
      ...)

   # S3 method for summary.Renouv
format(x,
      ...)

Arguments

object

An object with class "Renouv".

x

An object of class "summary.Renouv", i.e. a result of a call to summary.Renouv.

correlation

Logical; if TRUE, the correlation matrix of the estimated parameters is returned and printed.

coef

Logical. If FALSE, the table of coefficients and t-ratios' will not be printed.

pred

Logical. If FALSE, the table of return periods/levels will not be printed.

probT

If FALSE, the \(p\)-values for the t-tests will not be printed nor displayed.

digits

the number of significant digits to use when printing.

symbolic.cor

logical. If TRUE, print the correlations in a symbolic form (see symnum) rather than as numbers.

signif.stars

logical. If TRUE, ‘significance stars’ are printed for each coefficient.

...

Further arguments passed to or from other methods.

Details

print.summary.Renouv tries to be smart about formatting the coefficients, standard errors, return levels, etc. format.summary.Renouv returns as a limited content as a character string. It does not embed coefficients values nor predictions.

Value

The function summary.RenOUV computes and returns a list of summary statistics concerning the object of class "Rendata"

given in object. The returned list is an object with class

"summary.Renouv".

The function print.summary.Rendata does not returns anything.

Examples

## use Brest data
fit <- Renouv(Brest)
#> Special inference for the exponential case without history
#> Warning: uncertainty on the rate not taken into account yet  in the exponential with no history case

summary(fit)
#> o Main sample 'Over Threshold'
#>     . Threshold           30.00
#>     . Effect. duration   147.62 years
#>     . Nb. of exceed.    1289
#> 
#> o Estimated rate 'lambda' for Poisson process (events):  8.73 evt/year.
#> 
#> o Distribution for exceedances y: "exponential", with 1 par. "rate" 
#> 
#> o No transformation applied
#> 
#> o Coefficients
#> 
#>         Estimate  Std. Error  t value
#> lambda 8.7318791 0.243209905 35.90265
#> rate   0.0850335 0.002368447 35.90265
#> 
#> Degrees of freedom: 2 (param.) and 1289 (obs)
#> 
#> o Inference method used for return levels
#> "chi-square for exponential distribution (no historical data)"
#> 
#> o Return levels
#> 
#>    period quant L.95 U.95 L.70 U.70
#> 33     10    83   80   86   81   84
#> 35     20    91   88   94   89   93
#> 39     50   101   98  106   99  104
#> 41    100   110  105  114  107  112
#> 43    200   118  113  123  115  120
#> 46    300   123  118  128  120  125
#> 48    400   126  121  131  123  129
#> 49    500   129  123  134  126  131
#> 51    600   131  125  136  128  134
#> 52    700   133  127  138  130  136
#> 53    800   134  129  140  131  137
#> 54    900   135  130  141  133  139
#> 55   1000   137  131  143  134  140
#> 
#> 
#> o no 'MAX' historical data
#> 
#> o no 'OTS' historical data
#> 
#> o Kolmogorov-Smirnov test
#> 
#> 	Asymptotic one-sample Kolmogorov-Smirnov test
#> 
#> data:  OTjitter(y.OT, threshold = 0)
#> D = 0.021165, p-value = 0.6106
#> alternative hypothesis: two-sided
#> 
#> 
#> o Implied model for block maxima
#>   Distribution: gumbel 
#>   Coeffficients
#>      loc    scale 
#> 55.48385 11.76007