dev/LTPOPDTH.R
In timriffe/DemoTools: Standardize, Evaluate, and Adjust Demographic Data
# Author: tim
###############################################################################
#' Calculate an abridged-age lifetable.
#' @description Given vectors for Deaths and Exposures, or Mx, or qx, or lx, calculate a full abridged lifetable.
#'
#' @details The main variations here are in the treatment of \code{nAx}. In all cases, the lifetable is extended and closed out using one from a selection of mortality age extrapolation methods implemented in the \code{MortalityLaws} package. For this, a desired open age must be specified, defaulting to the present open age group, but which can not exceed 110 in the present implementation. By default, the extrapolation model is fit to ages 60 and higher, but you can control this using the \code{extrapFit} argument (give the vector of ages, which must be a subset of \code{Age}). By default extrapolated values are used starting with the input open age, but you can lower this age using the \code{extrapFrom} argument.
#'
#' @param Deaths numeric. Vector of death counts in abridged age classes.
#' @param Exposures numeric. Vector of population exposures in abridged age classes.
#' @param nMx numeric. Vector of mortality rates in abridged age classes.
#' @param nqx numeric. Vector of conditional death probabilities in abridged age classes.
#' @param lx numeric. Vector of lifetable survivorship at abridged ages.
#' @param AgeInt integer. Vector of age class widths. Default \code{inferAgeIntAbr(Age = Age)}.
#' @param radix numeric. Lifetable radix, \ifelse{html}{\out{l<sub>0}}{\eqn{l_0}}. Default 100000.
#' @param axmethod character. Either \code{"pas"} or \code{"un"}.
#' @param Sex character. Either male \code{"m"}, female \code{"f"}, or both \code{"b"}.
#' @param region character. North, East, South, or West: code{"n"}, code{"e"}, code{"s"}, code{"w"}. Default code{"w"}.
#' @param IMR numeric. Infant mortality rate \ifelse{html}{\out{q<sub>0}}{\eqn{q_0}}, in case available and \code{nqx} is not specified. Default \code{NA}.
#' @param mod logical. If \code{"un"} specified for \code{axmethod}, whether or not to use Nan Li's modification for ages 5-14. Default \code{TRUE}.
#' @param OAnew integer. Desired open age group (5-year ages only). Default \code{max(Age)}. If higher then rates are extrapolated.
#' @param OAG logical. Whether or not the last element of \code{nMx} (or \code{nqx} or \code{lx}) is an open age group. Default \code{TRUE}.
#' @param extrapLaw character. If extrapolating, which parametric mortality law should be invoked? Options include \code{"Kannisto", "Kannisto_Makeham", "Makeham","Gompertz", "GGompertz", "Beard", "Beard_Makeham", "Quadratic"}. Default \code{"Kannisto"}. See details.
#' @inheritParams aomegaMortalityLaws
#' @export
#' @return Lifetable in data.frame with columns
#' \itemize{
#' \item{Age}{integer. Lower bound of abridged age class},
#' \item{AgeInt}{integer. Age class widths.}
#' \item{nMx}{numeric. Age-specific central death rates.}
#' \item{nAx}{numeric. Average time spent in interval by those deceased in interval. }
#' \item{nqx}{numeric. Age-specific conditional death probabilities.}
#' \item{lx}{numeric. Lifetable survivorship}
#' \item{ndx}{numeric. Lifetable deaths distribution.}
#' \item{nLx}{numeric. Lifetable exposure.}
#' \item{Tx}{numeric. Lifetable total years left to live above age x.}
#' \item{ex}{numeric. Age-specific remaining life expectancy.}
#' }
#' @references
#' \insertRef{greville1977short}{DemoTools}
#' \insertRef{un1982model}{DemoTools}
#' \insertRef{arriaga1994population}{DemoTools}
#' \insertRef{mortpak1988}{DemoTools}
#' \insertRef{PAS}{DemoTools}
#'
#' @examples
# trial code from PAS LTPOPDTH, North, Males, IMR = .1
Exposures <- c(100958,466275,624134,559559,446736,370653,301862,249409,
247473,223014,172260,149338,127242,105715,79614,53660,
31021,16805,8000,4000,2000,1000)
Deaths <- c(8674,1592,618,411,755,1098,1100,1357,
1335,3257,2200,4023,2167,4578,2956,4212,
2887,2351,1500,900,500,300)
# lower age bounds
Age <- c(0, 1, seq(5, 100, by = 5))
AgeInt <- c(diff(Age), NA)
PASLT <- LTabr(Deaths = Deaths,
Exposures = Exposures,
Age = Age,
AgeInt = AgeInt,
axmethod = "pas",
IMR = .1,
region = "n",
Sex = "m",
OAG = T,
OAnew = max(Age))
# tail(PASLT)
# Deaths / Exposures
# 176.0660 / 513.3005
# 1 /2.915387
i <- length(PASLT$Age)
LT$nMx[i] <- mx[i]
LT$nAx[i] <- 1 / mx[i]
LT$nqx[i] <- NA
LT$nLx[i] <- LT$nAx[i] * LT$ndx[i]
LT$Tx[i] <- LT$nLx[i]
LT$ex[i] <- 1 / mx[i]
1/ PASLT$nMx[i]
# examples based on UN 1982 (p. 34)
Mx <- c(.23669,.04672,.00982,.00511,.00697,.01036,.01169,
.01332,.01528,.01757,.02092,.02517,.03225,.04241,.06056,
.08574,.11840,.16226,.23745)
excheckUN <- c(35.000,42.901,47.190,44.438,
40.523,36.868,33.691,30.567,27.500,24.485,21.504,18.599,
15.758,13.080,10.584,8.466,6.729,5.312,4.211)
AgeInt <- inferAgeIntAbr(vec = Mx)
# generate two variants: with and without PG's variants
# for ages 5-14
UNLT1 <- LTabr(nMx = Mx,
Age = c(0,1,seq(5,85,by=5)),
AgeInt = AgeInt,
axmethod = "un",
Sex = "m",
mod = FALSE)
UNLT2 <- LTabr(nMx = Mx,
Age = c(0,1,seq(5,85,by=5)),
AgeInt = AgeInt,
axmethod = "un",
Sex = "m",
mod = TRUE)
# \dontrun{
# plot(UNLT2$ex - UNLT1$ex)
# }
# a Mortpak unit test:
# data from p. 82 United Nations (1988) Mortpak - ...
MPnMx <- c(0.12846,0.02477,0.00603,0.0034,
0.00417,0.00513,0.00581,0.00645,0.00725,
0.00813,0.00913,0.01199,0.01647,
0.0256,0.04047,0.06624,0.10638,0.19611)
Age <- c(0,1,seq(5,80,by=5))
AgeInt <- age2int(Age,OAvalue = 5)
MPexcheck <- c(49.997,55.675,57.245,53.921,
49.803,45.799,41.922,38.084,34.249,
30.420,26.578,22.701,18.945,
15.349,12.095,9.240,6.903,5.099)
# First with lifetable extention to 100
MP_UNLT100 <- LTabr(
nMx = MPnMx,
Age = Age,
AgeInt = AgeInt,
axmethod = "un",
Sex = "f",
mod = FALSE,
OAnew = 100)
# lifetable to original open age group
MP_UNLT80 <- LTabr(
nMx = MPnMx,
Age = Age,
AgeInt = AgeInt,
axmethod = "un",
Sex = "f",
mod = FALSE,
OAnew = 80)
# same, but truncated at 60
MP_UNLT60 <- LTabr(
nMx = MPnMx,
Age = Age,
AgeInt = AgeInt,
axmethod = "un",
Sex = "f",
mod = FALSE,
OAnew = 60)
LTabr <- function(
Deaths,
Exposures,
nMx,
nqx,
lx,
Age,
AgeInt = age2int(Age = Age, OAvalue = 5),
radix = 1e5,
axmethod = "pas",
Sex = "m",
region = "w",
IMR = NA,
mod = TRUE,
OAG = TRUE,
OAnew = max(Age),
extrapLaw = c("Kannisto", "Kannisto_Makeham", "Makeham","Gompertz", "GGompertz", "Beard",
"Beard_Makeham", "Quadratic")[1],
extrapFrom = max(Age),
extrapFit = Age[Age >= 60],
...){
# this is a hard rule for now. May be relaxed if the
# ABACUS code is relaxed. For now mostly unmodified.
#stopifnot(OAnew <= 100)
# now overwriting raw nMx is allowed by lowering this
# arbitrary lower bound to accept the fitted model. Really
# this functionality is intended for extrapolation and not
# model overwriting of rates.
stopifnot(extrapFrom <= max(Age))
stopifnot(OAnew <= 110)
# need to make it possible to start w (D,E), M, q or l...
# 1) if lx given but not qx:
if (missing(nqx) & !missing(lx)){
nqx <- lx2dx(lx) / lx
}
# 2) if still no nqx then make sure we have or can get nMx
if (missing(nqx) & missing(nMx)){
stopifnot((!missing(Deaths)) & (!missing(Exposures)))
nMx <- Deaths / Exposures
}
# TR: what is this for?
# if (missing(Deaths)){
# Deaths <- NULL
# }
# if (missing(Exposures)){
# Exposures <- NULL
# }
axmethod <- tolower(axmethod)
Sex <- tolower(Sex)
region <- tolower(region)
extrapLaw <- tolower(extrapLaw)
# take care of ax first, two ways presently
if (missing(nMx)){
# TR: expedient hack
nqx[nqx > 1] <- 1
nAx <- mxorqx2ax(
nqx = nqx,
axmethod = axmethod,
Age = Age,
AgeInt = AgeInt,
Sex = Sex,
region = region,
OAG = OAG,
mod = mod,
IMR = IMR)
} else {
nAx <- mxorqx2ax(
nMx = nMx,
axmethod = axmethod,
Age = Age,
AgeInt = AgeInt,
Sex = Sex,
region = region,
OAG = OAG,
mod = mod,
IMR = IMR)
}
# # as of here we have nAx either way. And we have either mx or qx.
if (missing(nqx)){
nqx <- mxax2qx(nMx = nMx, nax = nAx, AgeInt = AgeInt, closeout = TRUE, IMR = IMR)
}
if (missing(nMx)){
nMx <- qxax2mx(nqx = nqx, nax = nAx, AgeInt = AgeInt)
}
# now we have all three, [mx,ax,qx] guaranteed.
# TR: save for later, in case OAG preserved
if (OAG & OAnew == max(Age)){
momega <- nMx[length(nMx)]
}
# --------------------------------
# begin extrapolation:
# TR: Oct 11, 2018: Deprecate abacus code, too hard to maintain. Variety of laws now avail
# no guarantee of monotonicity in old age however.
# TR: 13 Oct 2018. NOTE switch to always extrapolate to 130 no matter what,
# then truncate to OAnew in all cases. This will ensure more robust closeouts
# and an e(x) that doesn't depend on OAnew. 130 used in same way by HMD by the way.
OA <- max(Age)
x_extr <- seq(extrapFrom, 130, by = 5)
Mxnew <- extra_mortality(
x = Age,
mx = nMx,
x_fit = extrapFit,
x_extr = x_extr,
law = extrapLaw,
...)
nMxext <- Mxnew$values
Age2 <- names2age(nMxext)
keepi <- Age2 < extrapFrom
nMxext[keepi] <- nMx[Age < extrapFrom]
nMx <- nMxext
Age <- Age2
AgeInt <- age2int(Age,OAG=TRUE,OAvalue=max(AgeInt,na.rm=TRUE))
# redo ax and qx for extended ages
nAx <- mxorqx2ax(
nMx = nMx,
axmethod = axmethod,
Age = Age,
AgeInt = AgeInt,
Sex = Sex,
region = region,
OAG = TRUE,
mod = mod,
IMR = IMR)
nqx <- mxax2qx(
nMx = nMx,
nax = nAx,
AgeInt = AgeInt,
closeout = TRUE,
IMR = IMR)
# end extrapolation
# ---------------------------------
# TR: the lifetable is the shortest part of this code!
lx <- qx2lx(nqx, radix = radix)
ndx <- lx2dx(lx)
nLx <- lxdxax2Lx(lx = lx, ndx = ndx, nax = nAx, AgeInt = AgeInt)
Tx <- Lx2Tx(nLx)
ex <- Tx / lx
# TR: now cut down due to closeout method (added 11 Oct 2018)
ind <- Age <= OAnew
Age <- Age[ind]
AgeInt <- AgeInt[ind]
nAx <- nAx[ind]
nMx <- nMx[ind]
nqx <- nqx[ind]
lx <- lx[ind]
# recalc dx from chopped lx
ndx <- lx2dx(lx)
nLx <- nLx[ind]
Tx <- Tx[ind]
ex <- ex[ind]
# some closeout considerations
N <- length(nqx)
nqx[N] <- 1
nLx[N] <- Tx[N]
nAx[N] <- ex[N]
# TR: https://github.com/timriffe/DemoTools/issues/83
# (Added 3 Oct 2019)
if (OAG){
if (OAnew == max(Age)){
nMx[N] <- momega
} else {
# Otherwise inner coherence
nMx[N] <- lx[N] / Tx[N]
}
} else {
nMx[N] <- lx[N] / Tx[N]
}
# output is an unrounded, unsmoothed lifetable
out <- data.frame(
Age = Age,
AgeInt = AgeInt,
nMx = nMx,
nAx = nAx,
nqx = nqx,
lx = lx,
ndx = ndx,
nLx = nLx,
Tx = Tx,
ex = ex)
return(out)
}
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# Author: tim
###############################################################################
#' Calculate an abridged-age lifetable.
#' @description Given vectors for Deaths and Exposures, or Mx, or qx, or lx, calculate a full abridged lifetable.
#'
#' @details The main variations here are in the treatment of \code{nAx}. In all cases, the lifetable is extended and closed out using one from a selection of mortality age extrapolation methods implemented in the \code{MortalityLaws} package. For this, a desired open age must be specified, defaulting to the present open age group, but which can not exceed 110 in the present implementation. By default, the extrapolation model is fit to ages 60 and higher, but you can control this using the \code{extrapFit} argument (give the vector of ages, which must be a subset of \code{Age}). By default extrapolated values are used starting with the input open age, but you can lower this age using the \code{extrapFrom} argument.
#'
#' @param Deaths numeric. Vector of death counts in abridged age classes.
#' @param Exposures numeric. Vector of population exposures in abridged age classes.
#' @param nMx numeric. Vector of mortality rates in abridged age classes.
#' @param nqx numeric. Vector of conditional death probabilities in abridged age classes.
#' @param lx numeric. Vector of lifetable survivorship at abridged ages.
#' @param AgeInt integer. Vector of age class widths. Default \code{inferAgeIntAbr(Age = Age)}.
#' @param radix numeric. Lifetable radix, \ifelse{html}{\out{l<sub>0}}{\eqn{l_0}}. Default 100000.
#' @param axmethod character. Either \code{"pas"} or \code{"un"}.
#' @param Sex character. Either male \code{"m"}, female \code{"f"}, or both \code{"b"}.
#' @param region character. North, East, South, or West: code{"n"}, code{"e"}, code{"s"}, code{"w"}. Default code{"w"}.
#' @param IMR numeric. Infant mortality rate \ifelse{html}{\out{q<sub>0}}{\eqn{q_0}}, in case available and \code{nqx} is not specified. Default \code{NA}.
#' @param mod logical. If \code{"un"} specified for \code{axmethod}, whether or not to use Nan Li's modification for ages 5-14. Default \code{TRUE}.
#' @param OAnew integer. Desired open age group (5-year ages only). Default \code{max(Age)}. If higher then rates are extrapolated.
#' @param OAG logical. Whether or not the last element of \code{nMx} (or \code{nqx} or \code{lx}) is an open age group. Default \code{TRUE}.
#' @param extrapLaw character. If extrapolating, which parametric mortality law should be invoked? Options include \code{"Kannisto", "Kannisto_Makeham", "Makeham","Gompertz", "GGompertz", "Beard", "Beard_Makeham", "Quadratic"}. Default \code{"Kannisto"}. See details.
#' @inheritParams aomegaMortalityLaws
#' @export
#' @return Lifetable in data.frame with columns
#' \itemize{
#' \item{Age}{integer. Lower bound of abridged age class},
#' \item{AgeInt}{integer. Age class widths.}
#' \item{nMx}{numeric. Age-specific central death rates.}
#' \item{nAx}{numeric. Average time spent in interval by those deceased in interval. }
#' \item{nqx}{numeric. Age-specific conditional death probabilities.}
#' \item{lx}{numeric. Lifetable survivorship}
#' \item{ndx}{numeric. Lifetable deaths distribution.}
#' \item{nLx}{numeric. Lifetable exposure.}
#' \item{Tx}{numeric. Lifetable total years left to live above age x.}
#' \item{ex}{numeric. Age-specific remaining life expectancy.}
#' }
#' @references
#' \insertRef{greville1977short}{DemoTools}
#' \insertRef{un1982model}{DemoTools}
#' \insertRef{arriaga1994population}{DemoTools}
#' \insertRef{mortpak1988}{DemoTools}
#' \insertRef{PAS}{DemoTools}
#'
#' @examples
# trial code from PAS LTPOPDTH, North, Males, IMR = .1
Exposures <- c(100958,466275,624134,559559,446736,370653,301862,249409,
247473,223014,172260,149338,127242,105715,79614,53660,
31021,16805,8000,4000,2000,1000)
Deaths <- c(8674,1592,618,411,755,1098,1100,1357,
1335,3257,2200,4023,2167,4578,2956,4212,
2887,2351,1500,900,500,300)
# lower age bounds
Age <- c(0, 1, seq(5, 100, by = 5))
AgeInt <- c(diff(Age), NA)
PASLT <- LTabr(Deaths = Deaths,
Exposures = Exposures,
Age = Age,
AgeInt = AgeInt,
axmethod = "pas",
IMR = .1,
region = "n",
Sex = "m",
OAG = T,
OAnew = max(Age))
# tail(PASLT)
# Deaths / Exposures
# 176.0660 / 513.3005
# 1 /2.915387
i <- length(PASLT$Age)
LT$nMx[i] <- mx[i]
LT$nAx[i] <- 1 / mx[i]
LT$nqx[i] <- NA
LT$nLx[i] <- LT$nAx[i] * LT$ndx[i]
LT$Tx[i] <- LT$nLx[i]
LT$ex[i] <- 1 / mx[i]
1/ PASLT$nMx[i]
# examples based on UN 1982 (p. 34)
Mx <- c(.23669,.04672,.00982,.00511,.00697,.01036,.01169,
.01332,.01528,.01757,.02092,.02517,.03225,.04241,.06056,
.08574,.11840,.16226,.23745)
excheckUN <- c(35.000,42.901,47.190,44.438,
40.523,36.868,33.691,30.567,27.500,24.485,21.504,18.599,
15.758,13.080,10.584,8.466,6.729,5.312,4.211)
AgeInt <- inferAgeIntAbr(vec = Mx)
# generate two variants: with and without PG's variants
# for ages 5-14
UNLT1 <- LTabr(nMx = Mx,
Age = c(0,1,seq(5,85,by=5)),
AgeInt = AgeInt,
axmethod = "un",
Sex = "m",
mod = FALSE)
UNLT2 <- LTabr(nMx = Mx,
Age = c(0,1,seq(5,85,by=5)),
AgeInt = AgeInt,
axmethod = "un",
Sex = "m",
mod = TRUE)
# \dontrun{
# plot(UNLT2$ex - UNLT1$ex)
# }
# a Mortpak unit test:
# data from p. 82 United Nations (1988) Mortpak - ...
MPnMx <- c(0.12846,0.02477,0.00603,0.0034,
0.00417,0.00513,0.00581,0.00645,0.00725,
0.00813,0.00913,0.01199,0.01647,
0.0256,0.04047,0.06624,0.10638,0.19611)
Age <- c(0,1,seq(5,80,by=5))
AgeInt <- age2int(Age,OAvalue = 5)
MPexcheck <- c(49.997,55.675,57.245,53.921,
49.803,45.799,41.922,38.084,34.249,
30.420,26.578,22.701,18.945,
15.349,12.095,9.240,6.903,5.099)
# First with lifetable extention to 100
MP_UNLT100 <- LTabr(
nMx = MPnMx,
Age = Age,
AgeInt = AgeInt,
axmethod = "un",
Sex = "f",
mod = FALSE,
OAnew = 100)
# lifetable to original open age group
MP_UNLT80 <- LTabr(
nMx = MPnMx,
Age = Age,
AgeInt = AgeInt,
axmethod = "un",
Sex = "f",
mod = FALSE,
OAnew = 80)
# same, but truncated at 60
MP_UNLT60 <- LTabr(
nMx = MPnMx,
Age = Age,
AgeInt = AgeInt,
axmethod = "un",
Sex = "f",
mod = FALSE,
OAnew = 60)
LTabr <- function(
Deaths,
Exposures,
nMx,
nqx,
lx,
Age,
AgeInt = age2int(Age = Age, OAvalue = 5),
radix = 1e5,
axmethod = "pas",
Sex = "m",
region = "w",
IMR = NA,
mod = TRUE,
OAG = TRUE,
OAnew = max(Age),
extrapLaw = c("Kannisto", "Kannisto_Makeham", "Makeham","Gompertz", "GGompertz", "Beard",
"Beard_Makeham", "Quadratic")[1],
extrapFrom = max(Age),
extrapFit = Age[Age >= 60],
...){
# this is a hard rule for now. May be relaxed if the
# ABACUS code is relaxed. For now mostly unmodified.
#stopifnot(OAnew <= 100)
# now overwriting raw nMx is allowed by lowering this
# arbitrary lower bound to accept the fitted model. Really
# this functionality is intended for extrapolation and not
# model overwriting of rates.
stopifnot(extrapFrom <= max(Age))
stopifnot(OAnew <= 110)
# need to make it possible to start w (D,E), M, q or l...
# 1) if lx given but not qx:
if (missing(nqx) & !missing(lx)){
nqx <- lx2dx(lx) / lx
}
# 2) if still no nqx then make sure we have or can get nMx
if (missing(nqx) & missing(nMx)){
stopifnot((!missing(Deaths)) & (!missing(Exposures)))
nMx <- Deaths / Exposures
}
# TR: what is this for?
# if (missing(Deaths)){
# Deaths <- NULL
# }
# if (missing(Exposures)){
# Exposures <- NULL
# }
axmethod <- tolower(axmethod)
Sex <- tolower(Sex)
region <- tolower(region)
extrapLaw <- tolower(extrapLaw)
# take care of ax first, two ways presently
if (missing(nMx)){
# TR: expedient hack
nqx[nqx > 1] <- 1
nAx <- mxorqx2ax(
nqx = nqx,
axmethod = axmethod,
Age = Age,
AgeInt = AgeInt,
Sex = Sex,
region = region,
OAG = OAG,
mod = mod,
IMR = IMR)
} else {
nAx <- mxorqx2ax(
nMx = nMx,
axmethod = axmethod,
Age = Age,
AgeInt = AgeInt,
Sex = Sex,
region = region,
OAG = OAG,
mod = mod,
IMR = IMR)
}
# # as of here we have nAx either way. And we have either mx or qx.
if (missing(nqx)){
nqx <- mxax2qx(nMx = nMx, nax = nAx, AgeInt = AgeInt, closeout = TRUE, IMR = IMR)
}
if (missing(nMx)){
nMx <- qxax2mx(nqx = nqx, nax = nAx, AgeInt = AgeInt)
}
# now we have all three, [mx,ax,qx] guaranteed.
# TR: save for later, in case OAG preserved
if (OAG & OAnew == max(Age)){
momega <- nMx[length(nMx)]
}
# --------------------------------
# begin extrapolation:
# TR: Oct 11, 2018: Deprecate abacus code, too hard to maintain. Variety of laws now avail
# no guarantee of monotonicity in old age however.
# TR: 13 Oct 2018. NOTE switch to always extrapolate to 130 no matter what,
# then truncate to OAnew in all cases. This will ensure more robust closeouts
# and an e(x) that doesn't depend on OAnew. 130 used in same way by HMD by the way.
OA <- max(Age)
x_extr <- seq(extrapFrom, 130, by = 5)
Mxnew <- extra_mortality(
x = Age,
mx = nMx,
x_fit = extrapFit,
x_extr = x_extr,
law = extrapLaw,
...)
nMxext <- Mxnew$values
Age2 <- names2age(nMxext)
keepi <- Age2 < extrapFrom
nMxext[keepi] <- nMx[Age < extrapFrom]
nMx <- nMxext
Age <- Age2
AgeInt <- age2int(Age,OAG=TRUE,OAvalue=max(AgeInt,na.rm=TRUE))
# redo ax and qx for extended ages
nAx <- mxorqx2ax(
nMx = nMx,
axmethod = axmethod,
Age = Age,
AgeInt = AgeInt,
Sex = Sex,
region = region,
OAG = TRUE,
mod = mod,
IMR = IMR)
nqx <- mxax2qx(
nMx = nMx,
nax = nAx,
AgeInt = AgeInt,
closeout = TRUE,
IMR = IMR)
# end extrapolation
# ---------------------------------
# TR: the lifetable is the shortest part of this code!
lx <- qx2lx(nqx, radix = radix)
ndx <- lx2dx(lx)
nLx <- lxdxax2Lx(lx = lx, ndx = ndx, nax = nAx, AgeInt = AgeInt)
Tx <- Lx2Tx(nLx)
ex <- Tx / lx
# TR: now cut down due to closeout method (added 11 Oct 2018)
ind <- Age <= OAnew
Age <- Age[ind]
AgeInt <- AgeInt[ind]
nAx <- nAx[ind]
nMx <- nMx[ind]
nqx <- nqx[ind]
lx <- lx[ind]
# recalc dx from chopped lx
ndx <- lx2dx(lx)
nLx <- nLx[ind]
Tx <- Tx[ind]
ex <- ex[ind]
# some closeout considerations
N <- length(nqx)
nqx[N] <- 1
nLx[N] <- Tx[N]
nAx[N] <- ex[N]
# TR: https://github.com/timriffe/DemoTools/issues/83
# (Added 3 Oct 2019)
if (OAG){
if (OAnew == max(Age)){
nMx[N] <- momega
} else {
# Otherwise inner coherence
nMx[N] <- lx[N] / Tx[N]
}
} else {
nMx[N] <- lx[N] / Tx[N]
}
# output is an unrounded, unsmoothed lifetable
out <- data.frame(
Age = Age,
AgeInt = AgeInt,
nMx = nMx,
nAx = nAx,
nqx = nqx,
lx = lx,
ndx = ndx,
nLx = nLx,
Tx = Tx,
ex = ex)
return(out)
}
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