status level
In cascsim: Casualty Actuarial Society Individual Claim Simulator

Claim data fitting analysis at line/type/status level

claimFitting(object, claimData, ...)

## S4 method for signature 'Simulation,data.frame'
claimFitting(object, claimData,
  startDate = as.Date("2012-01-01"),
  evaluationDate = as.Date("2016-12-31"), lineList = object@lines,
  typeList = object@types, discreteDist = c("Poisson",
  "NegativeBinomial", "Geometric"), continuousDist = c("Normal",
  "Lognormal", "Pareto", "Weibull", "Gamma", "Uniform", "Exponential"),
  copulaList = c("normal"), fReportLag = TRUE, fSettlementLag = TRUE,
  fFrequency = TRUE, fSeverity = TRUE, fSSRCorrelation = TRUE,
  fFreqCorrelation = TRUE, copulaTest = TRUE, iTotalLoss = TRUE,
  fDeductible = TRUE, fLimit = TRUE, check = TRUE)

`object`	Simulation object
`claimData`	claim data including existing claims for RBNER and claim reopenness analysis
`...`	Additional parameters that may or may not be used.
`startDate`	Date after which claims are analyzed;
`evaluationDate`	Date of evaluation for existing claims and IBNR;
`lineList`	List of business lines to be included in claim fitting;
`typeList`	List of claim types to be included in claim fitting;
`discreteDist`	List of discrete distributions to try fitting (report lag, settlemet lag, frequency);
`continuousDist`	List of continuous distribution to try fitting (severity);
`copulaList`	List of copula to try fitting;
`fReportLag`	Boolean variable to indicate whether report lag needs to be fitted;
`fSettlementLag`	Boolean variable to indicate whether settlement lag needs to be fitted;
`fFrequency`	Boolean variable to indicate whether monthly frequency needs to be fitted;
`fSeverity`	Boolean variable to indicate whether severity needs to be fitted;
`fSSRCorrelation`	Boolean variable to indicate whether copula among severity, report lag and settlement lag needs to be fitted;
`fFreqCorrelation`	Boolean variable to indicate whether copula among frequencies of business lines needs to be fitted.
`copulaTest`	Whether to test copula. The testing could take a very long time;
`iTotalLoss`	Boolean variable to indicate whether total loss before deductible and limit is available for severity fitting;
`fDeductible`	Boolean variable to indicate whether deductible empirical distribution needs to be fitted;
`fLimit`	Boolean variable to indicate whether limit empirical distribution needs to be fitted;
`check`	Boolean variable to indicate whether graph of each tried distribution fitting needs to be generated and saved.

library(cascsim)
data(claimdata)
lines<-c("Auto")
types<-c("N")
#exposure index
index1 <- new("Index",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))),rep(1.4,301)))
#severity index
index2 <- new("Index",monthlyIndex=c(cumprod(c(1,rep(1.03^(1/12),59))),rep(1.03^(5),300)))
objan <- new("ClaimType", line="Auto",claimType="N",exposureIndex=index1,severityIndex=index2)
objlist <- list(objan)
simobj <- new("Simulation",lines=lines,types=types,claimobjs=objlist,iFit=TRUE,
iCopula=FALSE, iReport=TRUE, workingFolder=tempdir())
simobj <- claimFitting(simobj,claimdata,fSSRCorrelation = FALSE, fSettlementLag = FALSE)