View source: R/3_demographicFunctions.R
pxt | R Documentation |
These functions evaluate raw survival and death probabilities between age x and x+t
dxt(object, x, t, decrement)
pxt(object, x, t, fractional = "linear", decrement)
qxt(object, x, t, fractional = "linear", decrement)
object |
A |
x |
Age of life |
t |
Period until which the age shall be evaluated. Default value is 1.
(can be a vector for |
fractional |
Assumptions for fractional age. One of |
decrement |
The reason of decrement (only for |
Fractional assumptions are:
linear: linear interpolation between consecutive ages, i.e. assume uniform distribution.
constant force of mortality : constant force of mortality, also known as exponential interpolation.
hyperbolic: Balducci assumption, also known as harmonic interpolation.
Note that fractional="uniform"
, "exponential"
, "harmonic"
or "Balducci"
is also authorized.
See references for details.
A numeric value representing requested probability.
The function is provided as is, without any warranty regarding the accuracy of calculations. The author disclaims any liability for eventual losses arising from direct or indirect use of this software.
Function dxt
accepts also fractional value of t. Linear interpolation is used in such case. These functions are called by many other functions.
Giorgio A. Spedicato
Actuarial Mathematics (Second Edition), 1997, by Bowers, N.L., Gerber, H.U., Hickman, J.C., Jones, D.A. and Nesbitt, C.J.
exn
, lifetable
#dxt example
data(soa08Act)
dxt(object=soa08Act, x=90, t=2)
#qxt example
qxt(object=soa08Act, x=90, t=2)
#pxt example
pxt(object=soa08Act, x=90, t=2, "constant force" )
#add another example for MDT
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