Description Usage Arguments Details Value Methods (by class) Examples
Fit the full 2D extremal Poisson process for many thresholds
1 2 3 4 5 6 7 8 9 | fullMultiFit(x, lt, n_min, n_max, weight_scale, n_starts, progress_tf)
## S3 method for class 'declustered_series'
fullMultiFit(x, lt, n_min, n_max,
weight_scale, n_starts, progress_tf = TRUE)
## Default S3 method:
fullMultiFit(x, lt, n_min, n_max, weight_scale, n_starts,
progress_tf = TRUE)
|
x |
An S3 object of class |
lt |
(numeric scalar) The length of the time series in units of time (seconds, minutes, hours, etc.). |
n_min |
(numeric scalar) The minimum number of thresholded observations to include |
n_max |
(numeric scalar) The maximum number of thresholded observations to include |
weight_scale |
(numeric scalar) The value of τ |
n_starts |
(numeric scalar) The number of random starts to use in the search for the maximum |
progress_tf |
(logical scalar) Display a progress bar if TRUE, else not. |
fullMLE
and fullWPlot
are called for a sequence of
thresholds. Weights associated with each fit are also calculated. Suppose
that for threshold u_i the maximum vertical distance from a point on
the W plot to the 45^\circ line is δ_i such that the
δ_i are scaled to the unit interval. The weight
associated with threshold u_i is then
\frac{\exp\{-τδ_i\}}{∑\exp\{-τδ_i\}}
An S3 object of class full_multi_fit
with elements
$all_fits
An object of type full_pot_fit
for each
threshold
$thresholds
The thresholds for the fits
$weights
The weights associated with the fitted model for each threshold
$lt
The value of the lt
argument
$n_min
The value of the n_min
argument
$n_max
The value of the n_max
argument
$weight_scale
The value of the weight_scale
argument
declustered_series
:
default
:
1 2 3 4 5 6 7 8 | ## Not run:
ddat <- decluster(-jp1tap813wind315$value)
multi_est <- fullMultiFit(x = ddat, lt = 100, n_min = 10, n_max = 50, weight_scale = 5)
## End(Not run)
|
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