....

Description

....

Usage

PrecipitationAmountModel(x, valmin = 1, station = names(x),
  sample = "monthly", origin = "1961-1-1", ...)

Arguments

Value

The function returns AN S3 OBJECT ...... the correlation matrix of precipitation amount values (excluding the zeros). In case sample=="monthly" the runction return a MonlthyList S3 object.

See Also

predict.PrecipitationAmountModel,normalizeGaussian_severalstations

Examples

library(RGENERATEPREC)

set.seed(1245)

data(trentino)

year_min <- 1961
year_max <- 1990

origin <- paste(year_min,1,1,sep="-")
end <- paste(year_max,12,31,sep="-")

period <- PRECIPITATION$year>=year_min & PRECIPITATION$year<=year_max
period_temp <- TEMPERATURE_MAX$year>=year_min & TEMPERATURE_MAX$year<=year_max

prec_mes <- PRECIPITATION[period,]
Tx_mes <- TEMPERATURE_MAX[period_temp,]
Tn_mes <- TEMPERATURE_MIN[period_temp,]
accepted <- array(TRUE,length(names(prec_mes)))
names(accepted) <- names(prec_mes)
for (it in names(prec_mes)) {
	acc <- TRUE
	acc <- (length(which(!is.na(Tx_mes[,it])))==length(Tx_mes[,it]))
	acc <- (length(which(!is.na(Tn_mes[,it])))==length(Tn_mes[,it])) & acc
	accepted[it]  <- (length(which(!is.na(prec_mes[,it])))==length(prec_mes[,it])) & acc

}

valmin <- 1.0
prec_mes <- prec_mes[,accepted]



Tx_mes <- Tx_mes[,accepted]
Tn_mes <- Tn_mes[,accepted]
prec_occurence_mes <- prec_mes>=valmin

station <- names(prec_mes)[!(names(prec_mes) %in% c("day","month","year"))]

precamount <- PrecipitationAmountModel(prec_mes,station=station,origin=origin)

val <- predict(precamount)

prec_gen <- generate(precamount)




month <- adddate(as.data.frame(residuals(precamount$T0090)),origin=origin)$month
#####plot(month,residuals(precamount$T0090))
plot(factor(month),residuals(precamount$T0090))

qqplot(prec_mes$T0083,prec_gen$T0083)
abline(0,1)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(RGENERATEPREC)
Loading required package: copula
Loading required package: RGENERATE
Loading required package: RMAWGEN
Loading required package: chron
Loading required package: date
Loading required package: vars
Loading required package: MASS
Loading required package: strucchange
Loading required package: zoo

Attaching package: 'zoo'

The following objects are masked from 'package:base':

    as.Date, as.Date.numeric

Loading required package: sandwich
Loading required package: urca
Loading required package: lmtest

Attaching package: 'vars'

The following object is masked from 'package:copula':

    A

Loading required package: blockmatrix
Loading required package: Matrix
Loading required package: stringr

Attaching package: 'stringr'

The following object is masked from 'package:strucchange':

    boundary

> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/RGENERATEPREC/PrecipitationAmountModel.Rd_%03d_medium.png", width=480, height=480)
> ### Name: PrecipitationAmountModel
> ### Title: ....
> ### Aliases: PrecipitationAmountModel
> 
> ### ** Examples
> 
> library(RGENERATEPREC)
> 
> set.seed(1245)
> 
> data(trentino)
> 
> year_min <- 1961
> year_max <- 1990
> 
> origin <- paste(year_min,1,1,sep="-")
> end <- paste(year_max,12,31,sep="-")
> 
> period <- PRECIPITATION$year>=year_min & PRECIPITATION$year<=year_max
> period_temp <- TEMPERATURE_MAX$year>=year_min & TEMPERATURE_MAX$year<=year_max
> 
> prec_mes <- PRECIPITATION[period,]
> Tx_mes <- TEMPERATURE_MAX[period_temp,]
> Tn_mes <- TEMPERATURE_MIN[period_temp,]
> accepted <- array(TRUE,length(names(prec_mes)))
> names(accepted) <- names(prec_mes)
> for (it in names(prec_mes)) {
+ 	acc <- TRUE
+ 	acc <- (length(which(!is.na(Tx_mes[,it])))==length(Tx_mes[,it]))
+ 	acc <- (length(which(!is.na(Tn_mes[,it])))==length(Tn_mes[,it])) & acc
+ 	accepted[it]  <- (length(which(!is.na(prec_mes[,it])))==length(prec_mes[,it])) & acc
+ 
+ }
> 
> valmin <- 1.0
> prec_mes <- prec_mes[,accepted]
> 
> 
> 
> Tx_mes <- Tx_mes[,accepted]
> Tn_mes <- Tn_mes[,accepted]
> prec_occurence_mes <- prec_mes>=valmin
> 
> station <- names(prec_mes)[!(names(prec_mes) %in% c("day","month","year"))]
> 
> precamount <- PrecipitationAmountModel(prec_mes,station=station,origin=origin)
 Factor w/ 12 levels "1","2","3","4",..: 1 1 1 1 1 1 1 1 1 1 ...
 chr [1:10] "gamount" "T0014" "T0064" "T0083" "T0090" "T0129" ...
 chr [1:10] "gamount" "T0001" "T0064" "T0083" "T0090" "T0129" ...
 chr [1:10] "gamount" "T0001" "T0014" "T0083" "T0090" "T0129" ...
 chr [1:10] "gamount" "T0001" "T0014" "T0064" "T0090" "T0129" ...
 chr [1:10] "gamount" "T0001" "T0014" "T0064" "T0083" "T0129" ...
 chr [1:10] "gamount" "T0001" "T0014" "T0064" "T0083" "T0090" ...
 chr [1:10] "gamount" "T0001" "T0014" "T0064" "T0083" "T0090" ...
 chr [1:10] "gamount" "T0001" "T0014" "T0064" "T0083" "T0090" ...
 chr [1:10] "gamount" "T0001" "T0014" "T0064" "T0083" "T0090" ...
> 
> val <- predict(precamount)
> 
> prec_gen <- generate(precamount)
> 
> 
> 
> 
> month <- adddate(as.data.frame(residuals(precamount$T0090)),origin=origin)$month
> #####plot(month,residuals(precamount$T0090))
> plot(factor(month),residuals(precamount$T0090))
> 
> qqplot(prec_mes$T0083,prec_gen$T0083)
> abline(0,1)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>