Description Usage Arguments Value See Also Examples
View source: R/PrecipitationAmountModel.R
Creates a Precipitation Amount Model
1 2 3 4 5 6 7 8 | PrecipitationAmountModel(
x,
valmin = 1,
station = names(x),
sample = "monthly",
origin = "1961-1-1",
...
)
|
x |
observed precipitation amount time series (data frame) |
valmin |
maximum admitted value of precipitation depth |
station |
string vector containing station identification codes |
sample |
character string. If it is |
origin |
date of the day referred by he first row of |
... |
further agruments for |
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.
predict.PrecipitationAmountModel
,normalizeGaussian_severalstations
,generate
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 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 | 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_occurrence_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)
## SINGLE STATION
station <- "T0083"
precamount_single <- PrecipitationAmountModel(prec_mes,station=station,origin=origin)
val_single <- predict(precamount_single)
prec_gen_single <- generate(precamount_single)
month <- adddate(as.data.frame(residuals(precamount_single[[station[1]]])),origin=origin)$month
plot(factor(month),residuals(precamount_single[[station[1]]]))
### Comparison (Q-Q plot) between multi and single sites.
qqplot(prec_mes$T0083,prec_gen$T0083,col=1)
abline(0,1)
points(sort(prec_mes$T0083),sort(prec_gen_single$T0083),pch=2,col=2)
legend("bottomright",pch=c(1,2),col=c(1,2),legend=c("Multi Sites","Single Site"))
abline(0,1)
|
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