Description Usage Arguments Value Examples
Calculates regional (or local) parameters of a two-component GEV distribution (product of two GEVs) using (trimmed) L-moments (see TLMoments and parameters) from two vectors or two matrices of observation, e.g. winter and summer observations from one or more than one station. Based on these two parameter vectors, a p-quantile of the two-component GEV will be calculated for the jth station.
1 2 | RegioGEVSeas(x1, x2, p, j = 1, leftrim = 0, rightrim = 0, na.rm = TRUE,
...)
|
x1 |
vector or matrix of observations from season 1 (rows: observations, columns: stations). |
x2 |
vector or matrix of observations from season 2 (rows: observations, columns: stations). |
p |
a probability. |
j |
quantile and parameter estimation for the jth station (jth column of |
leftrim |
integer indicating lower trimming parameter (≥ 0). |
rightrim |
integer indicating upper trimming parameter (≥ 0). |
na.rm |
Should missing values be removed? |
... |
additional arguments, see TLMoments. |
List of
quant
quantile calculation from an estimated two-component GEV with a
regional (or local) shape-parameters.
param1
estimated parameter vector from season 1 from a GEV (using L-moments or trimmed L-moments).
param2
estimated parameter vector from season 2 from a GEV (using L-moments or trimmed L-moments).
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 26 27 28 29 30 | library("evd")
# Seasonal observations of 80 years at one station:
x1 <- rgev(80, 2, 1, 0.2) # observations from season 1
x2 <- rgev(80, 3, 1, 0.3) # observations from season 2
RegioGEVSeas(x1=x1, x2=x2, p=0.95)
# Missing values in both seasons in the same year(s):
x1a <- c(NA, x1, NA)
x2a <- c(NA, x2, NA)
RegioGEVSeas(x1a, x2a, p=0.99, leftrim=0, rightrim=0, na.rm=TRUE)
# Missing values in both seasons in different year(s):
x1b <- x1
x1b[c(4,19)] <- NA
x2b <- x2
x2b[77] <- NA
RegioGEVSeas(x1b, x2b, p=0.99, leftrim=0, rightrim=0, na.rm=TRUE)
# Seasonal observations of 100 years at 4 stations:
x1 <- matrix(rgev(400, 2, 1, 0.3), ncol=4)
x2 <- matrix(rgev(400, 4, 1, 0.2), ncol=4)
# estimate quantile for station 1 and 2 (consider the same shape-parameters):
RegioGEVSeas(x1, x2, p=0.99, j=1, leftrim=0, rightrim=0)
RegioGEVSeas(x1, x2, p=0.99, j=2, leftrim=0, rightrim=0)
# With missing values:
x3 <- x1
x4 <- x2
x3[c(54, 89, 300)] <- NA
RegioGEVSeas(x3, x4, p=0.99, j=1, leftrim=0, rightrim=0)
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