View source: R/PrecipitationOccurenceMultiSiteModel.R
PrecipitationOccurrenceMultiSiteModel | R Documentation |
This functions creates a stochastic Occurrence Multi-Site Model for the variable x
(PrecipitationOccurrenceMultiSiteModel
S3 object) through a calibration from observed data.
PrecipitationOccurrenceMultiSiteModel( x, exogen = NULL, station = names(x), origin = origin, valmin = 0.5, multisite_type = "wilks", tolerance_wilks = 0.001, p = 2, ... )
x |
data frame (each column is a site) of variable utilized for the auto-regression of its occurrence, e.g. daily precipitaton |
exogen |
exogenous predictors |
station |
character string vectors containing the codes of the station used for model calibration |
origin |
character string (yyyy-dd-mm) indicating the date of the first row of |
valmin |
minimum admitted value for daily precipitation amount |
multisite_type |
string indicating the utilized approach for spatial multi-site dependence description. Default is |
tolerance_wilks |
see |
p |
auto-regression order |
... |
further arguments |
The function returns a PrecipitationOccurrenceModel-class
S3 object containing the following elements:
... PrecipitationOccurrenceModel
S3 class objects for each analyzed site. The name is the site (or station) code
ccgama
CCGammaObjectListPerEachMonth
object, i.e. matices of Gaussian Inter-Site Correlation returned by CCGamma
;
type
string indicating the utilized approach for spatial multi-site dependence description, only "wilks"
type is implemented;
station
character string vectors containing the codes of the station used in PrecipitationMultiSiteOccurrenceModel
.
PrecipitationOccurrenceModel
,CCGamma
library(RGENERATEPREC) data(trentino) year_min <- 1961 year_max <- 1990 origin <- paste(year_min,1,1,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"))] station <- station[1:2] # to save example elapsed time!! exogen <- Tx_mes-Tn_mes months <- factor(prec_mes$month) #' ### Not Run!! # The following lines are commented to save example elapsed time!! model_multisite <- PrecipitationOccurrenceMultiSiteModel(x=prec_mes,exogen=exogen, origin=origin,multisite_type="wilks") ### Not Run!! # The following lines are commented to save example elapsed time!! model_multisite_logit <- PrecipitationOccurrenceMultiSiteModel(x=prec_mes,exogen=exogen, origin=origin,multisite_type="logit")
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