Diag_Non_Con_Trunc_Sel: Demonstrate the goodness of fit of the selected non-extreme...
In rjaneUCF/MultiHazard-R-Package: Tools for modeling compound events

Description Usage Arguments Value See Also Examples

Plots demonstrating the goodness of fit of a selected (truncated) non-extreme marginal distribution to a dataset.

1 2	Diag_Non_Con_Trunc_Sel(Data, x_lab, y_lim_min = 0, y_lim_max = 1, Selected)

`Data`	Numeric vector containing realizations of the variable of interest.
`x_lab`	Character vector of length one specifying the label on the x-axis of histogram and cummulative distribution plot.
`y_lim_min`	Numeric vector of length one specifying the lower y-axis limit of the histogram. Default is `0`.
`y_lim_max`	Numericr vector of length one specifying the upper y-axis limit of the histogram. Default is `1`.
`Selected`	Character vector of length one specifying the chosen distribution, options are the Birnbaum-Saunders `"BS"`, exponential `"Exp"`, gamma `"Gam"`, lognormal `"LogN"`, Tweedie `"Twe"` and Weibull `"Weib"`.

Panel consisting of three plots. Upper plot: Plot depicting the AIC of the eight fitted distributions. Middle plot: Probability Density Functions (PDFs) of the fitted distributions superimposed on a histogram of the data. Lower plot: Cumulative Distribution Functions (CDFs) of the fitted distributions overlaid on a plot of the empirical CDF.

Diag_Non_Con_Trunc

S20.OsWL<-Con_Sampling_2D(Data_Detrend=S20.Detrend.df[,-c(1,4)],
                          Data_Declust=S20.Detrend.Declustered.df[,-c(1,4)],
                          Con_Variable="OsWL",Thres=0.97)
Diag_Non_Con_Trunc(Data=S20.OsWL$Data$Rainfall,x_lab="Rainfall (Inches)",
                   y_lim_min=0,y_lim_max=2)
Diag_Non_Con_Sel_Trunc(Data=S20.OsWL$Data$Rainfall,x_lab="Rainfall (Inches)",
                       y_lim_min=0,y_lim_max=2,Selected="Twe")