Description Usage Arguments Details Value Author(s) References Examples
The T-return level is defined as the value of the observed variable that can be expected to be once exceeded during a T-period of time. This is computed as the quantile of the distribution, corresponding to the value F^{-1}(1-\frac{1}{T}).
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type_kernel |
The kernel function used. You can use four types: "e" Epanechnikov, "n" Normal, "b" Biweight and "t" Triweight. The Normal kernel is used by default. |
vec_data |
The data sample (earthquake magnitudes, flow levels, wind speeds... ). |
T |
A particular value of time, or an array of time values. |
bw |
The bandwidth parameter. The plug-in method of Polansky and Baker (2000) is used by default. |
In several scientific fields results of interest to estimate quantiles corresponding to a probability of exceedance. For example, in hydrology, the T-return level x_T is defined as the value of the observed flow that can be expected to be once exceeded during a T-period of time; that is, the quantile
x_T=F^{-1}(1-\frac{1}{T}).
We can estimate it directly by
\hat{x}_T=F_h^{-1}(1-\frac{1}{T}).
See, for instance, Quintela del Rio (2011), for an application to data of Salt River near Roosevelt, AZ, USA.
A single value or an array for the estimated quantiles.
Graciela Estevez Perez graci@udc.es and Alejandro Quintela del Rio aquintela@udc.es
Quintela-del-Rio, A. (2011) On bandwidth selection for nonparametric estimation in flood frequency analysis. Hydrological Processes 25, pp. 671–678.
Quintela-del-Rio, A. and Estevez-Perez, G. (2012) Nonparametric Kernel Distribution Function Estimation with kerdiest: An R Package for Bandwidth Choice and Applications, Journal of Statistical Software 50(8), pp. 1-21. URL http://www.jstatsoft.org/v50/i08/.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | data(saltriver)
peak<-saltriver$peakflow
## Not run:
year<-saltriver$year
plot(year,peak, type="l",ylab="Annual peak flow")
## End(Not run)
# Calculating the return values for a period from 2 to 100 years
T<-seq(2,100, length.out=100)
ret.lev<-rl(vec_data=peak, T=T)
## Not run:
plot(T, ret.lev, type="l", xlab="years", ylab="Flow (cumecs)",
main="Return level Plot")
## End(Not run)
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