R/A.R

In cascsim: Casualty Actuarial Society Individual Claim Simulator

#' setID
#' Set the ID for an object
#' @name setID<-
#' @param this Self
#' @param ... Additional function arguments
#' @param value ID
#' @examples
#' xindex <- new("Index")
#' setID(xindex)<-"IDX1"
#' xindex@indexID
#' @rdname setID-methods
#' @exportMethod setID<-
setGeneric("setID<-", function(this, ..., value) standardGeneric("setID<-"))

#' Set the start date for the claim simulation exercise
#' @name setStartDate<-
#' @param this Self
#' @param ... Additional function arguments
#' @param value Start Date
#' @rdname setStartDate-methods
setGeneric("setStartDate<-", function(this, ..., value) standardGeneric("setStartDate<-"))

#' Input the raw data.
#' @name setObservation<-
#' @param this FitDist Object or Copula Object
#' @param value A data frame or a matrix. For FitDist object, it could be a two-column data frame with the occurrence date and loss size/number of occurrence. Or a one-column data frame with loss size (ifreq == FALSE) or number of occurrence (ifreq == TRUE && idate == FALSE) or occurrence dates (ifreq == TRUE && idate == TRUE). For Copula object, it could be a matrix with each column contains the experience data of a variable.
#' @examples
#' library(cascsim)
#' dist1<-new("Pareto",p1=20,p2=3)
#' dist2<-new("Normal",p1=5,p2=3,min=0,max=20,truncated=TRUE)
#' nom.cop <- new("CopulaObj", param=c(0.5),marginal=list(dist1=dist1,dist2=dist2),dimension=2)
#' setObservation(nom.cop)<-copulaSample(nom.cop,100)
#' nom.cop@observation
#' @rdname setObservation-methods
#' @export setObservation<-
setGeneric("setObservation<-", function(this,value) standardGeneric("setObservation<-"))

setGeneric("toString", function(object, ...) standardGeneric("toString"))

#' Density function.
#' @name Density
#' @param object Distribution Object
#' @param x Variable value
#' @param ... Additional function arguments
#' @examples
#' xPareto <- new("Pareto",p1=20,p2=3)
#' Density(xPareto,50)
#' @rdname Density-methods
#' @exportMethod Density
setGeneric("Density", function(object, x, ...) standardGeneric("Density"))

#' Probability function.
#' @name Probability
#' @param object Distribution Object
#' @param q Variable value
#' @param ... Additional function arguments
#' @examples
#' xPareto <- new("Pareto",p1=20,p2=3)
#' Probability(xPareto,50)
#' @rdname Probability-methods
#' @exportMethod Probability
setGeneric("Probability", function(object, q, ...) standardGeneric("Probability"))

#' Quantile function.
#' @name Quantile
#' @param object Distribution Object
#' @param p Probability
#' @param ... Additional function arguments
#' @examples
#' xPareto <- new("Pareto",p1=20,p2=3)
#' Quantile(xPareto,0.6)
#' @rdname Quantile-methods
#' @export Quantile
setGeneric("Quantile", function(object, p, ...) standardGeneric("Quantile"))

#' Plot function.
#' @name doPlot
#' @param object Object
#' @param ... Additional function arguments
#' @examples
#' xPareto <- new("Pareto",p1=20,p2=3)
#' doPlot(xPareto)
#' @rdname doPlot-methods
#' @exportMethod doPlot
setGeneric("doPlot", function(object, ...) standardGeneric("doPlot"))

#' Get input data from an object.
#' @name getObservation
#' @param object Object
#' @param ... Additional function arguments
#' @examples
#' library(cascsim)
#' data(claimdata)
#'
#' #frequecy fitting example
#' findex <- new("Index", startDate = as.Date("2012-01-01"), tabulate=TRUE, monthlyIndex = c(rep(1,11),
#' cumprod(c(1,rep(1.5^(1/12),11))),cumprod(c(1.5,rep((1.3/1.5)^(1/12),11))),
#' cumprod(c(1.3,rep((1.35/1.3)^(1/12),11))),cumprod(c(1.35,rep((1.4/1.35)^(1/12),11))),1.4))
#' rawdata <- as.data.frame(as.Date(claimdata[(claimdata[,"LoB"]=="Auto" & 
#' claimdata[,"Type"]=="H"),]$occurrenceDate))
#' colnames(rawdata)<-"occurrenceDate"
#' xFit <- new("FitDist", observation=rawdata, trend=findex,startDate = as.Date("2012-01-01"),
#' method="mle",ifreq=TRUE,idate=TRUE, freq="Monthly")
#' getObservation(xFit)
#' @rdname getObservation-methods
#' @exportMethod getObservation
setGeneric("getObservation", function(object,...) standardGeneric("getObservation"))

#' Get the trend index.
#' @name getTrend
#' @param object Object
#' @param ... Additional function arguments
#' @examples
#' library(cascsim)
#' data(claimdata)
#'
#' #frequecy fitting example
#' findex <- new("Index", startDate = as.Date("2012-01-01"), tabulate=TRUE, monthlyIndex = c(rep(1,11),
#' cumprod(c(1,rep(1.5^(1/12),11))),cumprod(c(1.5,rep((1.3/1.5)^(1/12),11))),
#' cumprod(c(1.3,rep((1.35/1.3)^(1/12),11))),cumprod(c(1.35,rep((1.4/1.35)^(1/12),11))),1.4))
#' rawdata <- as.data.frame(as.Date(claimdata[(claimdata[,"LoB"]=="Auto" & 
#' claimdata[,"Type"]=="H"),]$occurrenceDate))
#' colnames(rawdata)<-"occurrenceDate"
#' xFit <- new("FitDist", observation=rawdata, trend=findex,startDate = as.Date("2012-01-01"),
#' method="mle",ifreq=TRUE,idate=TRUE, freq="Monthly")
#' getTrend(xFit)
#' @rdname getTrend-methods
#' @exportMethod getTrend
setGeneric("getTrend", function(object,...) standardGeneric("getTrend"))