lifecontingencies (version 1.3.12)

rLifeContingencies: Function to generate samples from the life contingencies stochastic variables

Description

Function to generate samples from the life contingencies stochastic variables

Usage

rLifeContingencies(
  n,
  lifecontingency,
  object,
  x,
  t,
  i = object@interest,
  m = 0,
  k = 1,
  parallel = FALSE,
  payment = "advance"
)
rLifeContingenciesXyz(
  n,
  lifecontingency,
  tablesList,
  x,
  t,
  i,
  m = 0,
  k = 1,
  status = "joint",
  parallel = FALSE,
  payment = "advance"
)

Value

A numeric vector

Arguments

n

Size of sample

lifecontingency

A character string, either "Exn", "Axn", "axn", "IAxn" or "DAxn"

object

An actuarialtable object.

x

Policyholder's age at issue time; for rLifeContingenciesXyz a numeric vector of the same length of object, containing the policyholders' ages

t

The lenght of the insurance. Must be specified according to the present value of benefits definition.

i

The interest rate, whose default value is the actuarialtable interest rate slot value.

m

Deferring period, default value is zero.

k

Fractional payment, default value is 1.

parallel

Uses the parallel computation facility.

payment

The Payment type, either "advance" for the annuity due (default) or "arrears" for the annuity immediate. Alternatively, one can use "due" or "immediate" respectively (can be abbreviated).

tablesList

A list of actuarialtable objects

status

Either "joint" for the joint-life status model or "last" for the last-survivor status model (can be abbreviated).

Examples

if (FALSE) {
	#assumes SOA example life table to be load
	data(soaLt)
	soa08Act=with(soaLt, new("actuarialtable",interest=0.06, x=x,lx=Ix,name="SOA2008"))
	out<-rLifeContingencies(n=1000, lifecontingency="Axn",object=soa08Act, x=40,
	t=getOmega(soa08Act)-40, m=0)
	APV=Axn(soa08Act,x=40)
	#check if out distribution is unbiased
	t.test(x=out, mu=APV)$p.value>0.05
}
if (FALSE) {
data(soa08Act)
n=10000
lifecontingency="Axyz"
tablesList=list(soa08Act,soa08Act)
x=c(60,60); i=0.06; m=0; status="joint"; t=30; k=1
APV=Axyzn(tablesList=tablesList,x=x,n=t,m=m,k=k,status=status,type="EV")
samples<-rLifeContingenciesXyz(n=n,lifecontingency = lifecontingency,tablesList = tablesList,
x=x,t=t,m=m,k=k,status=status, parallel=FALSE)
APV
mean(samples)
}