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step-4a-function-CV-and-Forecast-CPM.R
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#######################################################################
#######################################################################
## 'validate-forecast-methods' is a program that provides the R source code
## used for the calculations in the project:
## Bohk-Ewald, Christina, Peng Li, and Mikko Myrskylä (2017).
## Assessing the accuracy of cohort fertility forecasts.
## Presented in session: Statistical methods in demography
## at the PAA 2017 Annual Meeting, Chicago, IL, USA, April 27-April 29, 2017.
## (c) Copyright 2018, Christina Bohk-Ewald, Peng Li, Mikko Myrskylä
## This program is free software: you can redistribute it and/or modify
## it under the terms of the GNU General Public License as published by
## the Free Software Foundation, either version 3 of the License, or
## (at your option) any later version.
## This program is distributed in the hope that it will be useful,
## but WITHOUT ANY WARRANTY; without even the implied warranty of
## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
## GNU General Public License for more details.
## You should have received a copy of the GNU General Public License
## along with this program (see LICENSE.txt in the root of this source code).
## If not, see <http://www.gnu.org/licenses/>.
#######################################################################
#######################################################################
#########################################################################################################################
# CV
#
#
#
#
#
#
#
#
#
#########################################################################################################################
########
write_CPMobj_to_file <- function(CPMobj,folder=NA,pop,header="obj"){
if(!dir.exists(folder))
dir.create(folder)
flag <- paste(header,CPMobj$label,"obs",CPMobj$obs,"joy",CPMobj$year[2],"len",CPMobj$len,CPMobj$pop,sep="_")
save(CPMobj,file = ifelse(!is.na(folder),file.path(folder,paste(flag,".Rdata",sep="")),paste(flag,".Rdata",sep="")))
}
########
write_CPMobjlist_to_file <- function(CPMobjlist,folder=NA,header="list"){
if(!dir.exists(folder))
dir.create(folder)
flag <- paste(header,CPMobjlist[[1]]$label,"obs",CPMobjlist[[1]]$obs,"joy",CPMobjlist[[1]]$year[2],"len",CPMobjlist[[1]]$len,sep="_")
save(CPMobjlist,file = ifelse(!is.na(folder),file.path(folder,paste(flag,".Rdata",sep="")),paste(flag,".Rdata",sep="")))
}
########
##########################################################
asfr_period_to_cohort <- function(input){
temp <- expand.grid(as.numeric(dimnames(input)[[1]]),as.numeric(dimnames(input)[[2]]))
cohort <- temp[,2] - temp[,1]
output <- tapply(as.vector(as.matrix(input)), list(temp[,1], cohort),sum)
return(as.data.frame(output))
}
asfr_cohort_to_period <- function(input,clean=T){
temp <- expand.grid(as.numeric(dimnames(input)[[1]]),as.numeric(dimnames(input)[[2]]))
period <- temp[,2] + temp[,1]
output <- tapply(as.vector(as.matrix(input)), list(temp[,1], period),sum)
if(clean){
output <- output[,!apply(output,2,function(x) all(is.na(x)))]
}
return(as.data.frame(output))
}
###########################################################
extract_obs_pred_data <- function(CVobse,CVpred,age1=15,age2=40,AAF1=20,AAF2=age2-1,flag="test",out=""){
pop_names <- dimnames(CVobse)[[3]]
names(pop_names) <- pop_names
cfr_observed <- array(NA,dim=c(length(AAF1:AAF2),length(pop_names),length(1895:2014)),dimnames=list(AAF1:AAF2,pop_names,2014:1895))
cfr_forecast <- array(NA,dim=c(length(AAF1:AAF2),length(pop_names),length(1895:2014)),dimnames=list(AAF1:AAF2,pop_names,2014:1895))
for(pop in pop_names){
#print(pop)
temp <- CVobse[,,pop]
period <- as.numeric(names(temp[1,])[!is.na(temp[1,])])
ctemp <- asfr_period_to_cohort(temp)
pred <- CVpred[pop,,,]
years <- as.numeric(dimnames(pred)[[1]])
for(joy in years){
for(AAF in AAF1:AAF2){
####
#print(c(AAF,joy,joy-AAF))
cfr_observed[as.character(AAF), pop_names[pop],as.character(joy)] <- sum(ctemp[as.character(age1:age2),as.character(joy-AAF)])
cfr_forecast[as.character(AAF), pop_names[pop],as.character(joy)] <- sum(pred[as.character(joy),as.character(age1:age2),as.character(joy-AAF)])
}
}
}
file <- file.path(out,paste(flag,"_cfr_CVobse.Rdata",sep=""))
save(cfr_observed,file = file)
file <- file.path(out,paste(flag,"_cfr_CVpred.Rdata",sep=""))
save(cfr_forecast,file = file)
}
###########################################################
save_observed_predicted_cfr <- function(asfr_period_data,obs=obs,age1=15,age2=40,parameter= c("linear","arima"),len=50,name="CoaleTrussell",file.head="Forecastlist",folder=""){
label <- ifelse(all(!is.na(parameter)),paste(name,paste(parameter,collapse = "_"),sep="_"),name)
if(name == "")
label <- ifelse(all(!is.na(parameter)),paste(paste(parameter,collapse = "_"),sep="_"),name)
flag <- paste("Forecastlist",label,"obs",obs,"len",len,sep="_")
file <- file.path(folder,paste(flag,"_CVpredCASFR.Rdata",sep=""))
if(exists("CVpredCASFR")){
rm("CVpredCASFR")
}
if(exists("cfr_forecast")){
rm("cfr_forecast")
}
load(file)
cat("Calculate CFR...")
####
extract_obs_pred_data(CVobse =asfr_period_data, CVpred = CVpredCASFR,flag="Result",age1=age1,age2=40,out=folder)
cat("done.\n")
}
########################
# Cross-validation
########################
CV_CPM_ASFR_function <- function(FUN, asfr_period_hfd,joy=2010,obs=30,age1=15,age2=44,parameter=NA,len=50,folder=NA,out=F){
CPMobjlist <- apply(asfr_period_hfd,3,FUN,joy,obs,age1,age2,parameter,len)
for(pop in dimnames(asfr_period_hfd)[[3]]){
CPMobjlist[[pop]]$pop <- pop
}
if(!is.na(folder)){
write_CPMobjlist_to_file(CPMobjlist,folder,header="Forecastlist")
}
if(out){
return(CPMobjlist)
}
}
if(0>1){
source("Scripts/Method00_FreezeRate/Method00_FreezeRate.R")
pop = "AUT"
ASFR = asfr_period_hfd[,,pop]
joy = 1995
obs = 30
age1 = 15
age2 = 44
parameter = NA
len = 50
CV_CPM_ASFR_function(Method00_FreezeRate.R,asfr_period_hfd,joy=2010,obs=30,age1=15,age2=44,parameter=NA,len=50,folder="Temp")
}
########################
# Real-forecast
########################
Forecast_CPM_ASFR_function <- function(FUN, asfr_period_hfd,joy=NA,obs=30,age1=15,age2=44,parameter=NA,len=50,folder=NA,out=F){
#CPMobjlist <- apply(asfr_period_hfd,3,FUN,joy=NA,obs,age1,age2,parameter,len)
#for(pop in dimnames(asfr_period_hfd)[[3]]){
# CPMobjlist[[pop]]$pop <- pop
#}
CPMobjlist <- list()
for(pop in dimnames(asfr_period_hfd)[[3]]){
#print(pop)
CPMobjlist[[pop]] <- FUN(asfr_period_hfd[,,pop],joy,obs,age1,age2,parameter,len,pop)
CPMobjlist[[pop]]$pop <- pop
}
if(!is.na(folder)){
write_CPMobjlist_to_file(CPMobjlist,folder,header="Forecastlist")
}
if(out){
return(CPMobjlist)
}
}
if(0>1){
source("Scripts/Method00_FreezeRate/Method00_FreezeRate.R")
pop = "AUT"
ASFR = asfr_period_hfd[,,pop]
joy = 1995
obs = 30
age1 = 15
age2 = 44
parameter = NA
len = 50
test <- Forecast_CPM_ASFR_function(Method00_FreezeRate.R,asfr_period_hfd,joy=NA,obs=30,age1=15,age2=44,parameter=NA,len=50,folder="Temp",out=T)
}
Forecast_CPM_ASFR_EXPOS_function <- function(FUN, asfr_period_hfd,expos_period_hfd,joy=NA,obs=30,age1=15,age2=44,parameter=NA,len=50,folder=NA,out=F){
CPMobjlist <- list()
for(pop in dimnames(asfr_period_hfd)[[3]]){
CPMobjlist[[pop]] <- FUN(asfr_period_hfd[,,pop],expos_period_hfd[,,pop],joy,obs,age1,age2,parameter,len,pop)
CPMobjlist[[pop]]$pop <- pop
}
if(!is.na(folder)){
write_CPMobjlist_to_file(CPMobjlist,folder,header="Forecastlist")
}
if(out){
return(CPMobjlist)
}
}
##################################################
Extract_CPM_ASFR_function <- function(JOY=1936:2014,obs=obs,age1=15,age2=44,parameter= c("linear","arima"),len=50,name="CoaleTrussell",file.head="Forecastlist",full_names=full_names,folder="Results/CV/Method03_CoaleTrussell1974",out="Results/CV",remove_raw=T){
CVpredASFR <- array(NA,dim=c(length(full_names),length(1936:2014),length(age1:age2),length(1895:2050)),dimnames=list(names(full_names),1936:2014,age1:age2,1895:2050))
cohorts <- colnames(asfr_period_to_cohort(CVpredASFR[1,1,,]))
CVpredCASFR <- array(NA,dim=c(length(full_names),length(1936:2014),length(age1:age2),length(cohorts)),dimnames=list(names(full_names),1936:2014,age1:age2,cohorts))
cat("Extract results")
joy <- JOY[1]
for(joy in JOY){
if(name != "")
label <- ifelse(all(!is.na(parameter)),paste(name,paste(parameter,collapse = "_"),sep="_"),name)
if(name == "")
label <- ifelse(all(!is.na(parameter)),paste(paste(parameter,collapse = "_"),sep="_"),name)
flag <- paste(file.head,label,"obs",obs,"joy",joy,"len",len,sep="_")
file <- file.path(folder,paste(flag,".Rdata",sep=""))
load(file)
#cat(joy," ")
for(pop in names(full_names)){
#print(pop)
temp <- as.matrix(CPMobjlist[[which(names(CPMobjlist) == pop)]][[4]])
#print(temp)
#colnames(temp) <- paste(age1:age2)
if(any(!is.na(temp))){
CVpredASFR[pop,paste(joy),rownames(temp),intersect(colnames(temp),paste(1895:2050))] <- temp[,intersect(colnames(temp),paste(1895:2050))]
}
temp <- as.matrix(CPMobjlist[[which(names(CPMobjlist) == pop)]][[5]])
#print(temp)
if(any(!is.na(temp))){
CVpredCASFR[pop,paste(joy),rownames(temp),intersect(colnames(temp),paste(cohorts))] <- temp[,intersect(colnames(temp),paste(cohorts))]
}
}
####
if(remove_raw){
unlink(file, recursive = FALSE, force = FALSE)
}
}
flag <- paste("Forecastlist",label,"obs",obs,"len",len,sep="_")
file <- file.path(out,paste(flag,"_CVpredASFR.Rdata",sep=""))
save(CVpredASFR,file = file)
file <- file.path(out,paste(flag,"_CVpredCASFR.Rdata",sep=""))
save(CVpredCASFR,file = file)
cat("\n")
}
##############################################################
Extract_CPM_ASFR_PI_function <- function(JOY=1936:2014,obs=obs,age1=15,age2=44,parameter= c("linear","arima"),len=50,name="CoaleTrussell",file.head="Forecastlist",full_names=full_names,folder="Results/CV/Method03_CoaleTrussell1974",out="Results/CV"){
CVpredASFR <- array(NA,dim=c(length(full_names),length(1936:2014),length(age1:age2),length(1895:2050)),dimnames=list(names(full_names),1936:2014,age1:age2,1895:2050))
cohorts <- colnames(asfr_period_to_cohort(CVpredASFR[1,1,,]))
CVpredCASFR <- array(NA,dim=c(length(full_names),length(1936:2014),length(age1:age2),length(cohorts)),dimnames=list(names(full_names),1936:2014,age1:age2,cohorts))
CVpredASFRlowerPI80 <- array(NA,dim=c(length(full_names),length(1936:2014),length(age1:age2),length(1895:2050)),dimnames=list(names(full_names),1936:2014,age1:age2,1895:2050))
CVpredASFRlowerPI95 <- array(NA,dim=c(length(full_names),length(1936:2014),length(age1:age2),length(1895:2050)),dimnames=list(names(full_names),1936:2014,age1:age2,1895:2050))
CVpredASFRupperPI80 <- array(NA,dim=c(length(full_names),length(1936:2014),length(age1:age2),length(1895:2050)),dimnames=list(names(full_names),1936:2014,age1:age2,1895:2050))
CVpredASFRupperPI95 <- array(NA,dim=c(length(full_names),length(1936:2014),length(age1:age2),length(1895:2050)),dimnames=list(names(full_names),1936:2014,age1:age2,1895:2050))
cohorts <- colnames(asfr_period_to_cohort(CVpredASFR[1,1,,]))
CVpredCASFRlowerPI80 <- array(NA,dim=c(length(full_names),length(1936:2014),length(age1:age2),length(cohorts)),dimnames=list(names(full_names),1936:2014,age1:age2,cohorts))
CVpredCASFRlowerPI95 <- array(NA,dim=c(length(full_names),length(1936:2014),length(age1:age2),length(cohorts)),dimnames=list(names(full_names),1936:2014,age1:age2,cohorts))
CVpredCASFRupperPI80 <- array(NA,dim=c(length(full_names),length(1936:2014),length(age1:age2),length(cohorts)),dimnames=list(names(full_names),1936:2014,age1:age2,cohorts))
CVpredCASFRupperPI95 <- array(NA,dim=c(length(full_names),length(1936:2014),length(age1:age2),length(cohorts)),dimnames=list(names(full_names),1936:2014,age1:age2,cohorts))
joy <- JOY[1]
for(joy in JOY){
if(name != "")
label <- ifelse(all(!is.na(parameter)),paste(name,paste(parameter,collapse = "_"),sep="_"),name)
if(name == "")
label <- ifelse(all(!is.na(parameter)),paste(paste(parameter,collapse = "_"),sep="_"),name)
flag <- paste(file.head,label,"obs",obs,"joy",joy,"len",len,sep="_")
file <- file.path(folder,paste(flag,".Rdata",sep=""))
load(file)
print(joy)
for(pop in names(full_names)){
print(pop)
temp <- as.matrix(CPMobjlist[[which(names(CPMobjlist) == pop)]][[7]])
if(any(!is.na(temp))){
CVpredASFRlowerPI80[pop,paste(joy),rownames(temp),intersect(colnames(temp),paste(1895:2050))] <- temp[,intersect(colnames(temp),paste(1895:2050))]
}
temp <- as.matrix(CPMobjlist[[which(names(CPMobjlist) == pop)]][[11]])
if(any(!is.na(temp))){
CVpredASFRlowerPI95[pop,paste(joy),rownames(temp),intersect(colnames(temp),paste(1895:2050))] <- temp[,intersect(colnames(temp),paste(1895:2050))]
}
temp <- as.matrix(CPMobjlist[[which(names(CPMobjlist) == pop)]][[9]])
if(any(!is.na(temp))){
CVpredASFRupperPI80[pop,paste(joy),rownames(temp),intersect(colnames(temp),paste(1895:2050))] <- temp[,intersect(colnames(temp),paste(1895:2050))]
}
temp <- as.matrix(CPMobjlist[[which(names(CPMobjlist) == pop)]][[13]])
if(any(!is.na(temp))){
CVpredASFRupperPI95[pop,paste(joy),rownames(temp),intersect(colnames(temp),paste(1895:2050))] <- temp[,intersect(colnames(temp),paste(1895:2050))]
}
########
temp <- as.matrix(CPMobjlist[[which(names(CPMobjlist) == pop)]][[6]])
if(any(!is.na(temp))){
CVpredCASFRlowerPI80[pop,paste(joy),rownames(temp),intersect(colnames(temp),paste(cohorts))] <- temp[,intersect(colnames(temp),paste(cohorts))]
}
temp <- as.matrix(CPMobjlist[[which(names(CPMobjlist) == pop)]][[10]])
if(any(!is.na(temp))){
CVpredCASFRlowerPI95[pop,paste(joy),rownames(temp),intersect(colnames(temp),paste(cohorts))] <- temp[,intersect(colnames(temp),paste(cohorts))]
}
temp <- as.matrix(CPMobjlist[[which(names(CPMobjlist) == pop)]][[8]])
if(any(!is.na(temp))){
CVpredCASFRupperPI80[pop,paste(joy),rownames(temp),intersect(colnames(temp),paste(cohorts))] <- temp[,intersect(colnames(temp),paste(cohorts))]
}
temp <- as.matrix(CPMobjlist[[which(names(CPMobjlist) == pop)]][[12]])
if(any(!is.na(temp))){
CVpredCASFRupperPI95[pop,paste(joy),rownames(temp),intersect(colnames(temp),paste(cohorts))] <- temp[,intersect(colnames(temp),paste(cohorts))]
}
}
}
flag <- paste("Forecastlist",label,"obs",obs,"len",len,sep="_")
file <- file.path(out,paste(flag,"_CVpredASFRlowerPI80.Rdata",sep=""))
save(CVpredASFRlowerPI80,file = file)
file <- file.path(out,paste(flag,"_CVpredASFRlowerPI95.Rdata",sep=""))
save(CVpredASFRlowerPI95,file = file)
file <- file.path(out,paste(flag,"_CVpredASFRupperPI80.Rdata",sep=""))
save(CVpredASFRupperPI80,file = file)
file <- file.path(out,paste(flag,"_CVpredASFRupperPI95.Rdata",sep=""))
save(CVpredASFRupperPI95,file = file)
file <- file.path(out,paste(flag,"_CVpredCASFRlowerPI80.Rdata",sep=""))
save(CVpredCASFRlowerPI80,file = file)
file <- file.path(out,paste(flag,"_CVpredCASFRlowerPI95.Rdata",sep=""))
save(CVpredCASFRlowerPI95,file = file)
file <- file.path(out,paste(flag,"_CVpredCASFRupperPI80.Rdata",sep=""))
save(CVpredCASFRupperPI80,file = file)
file <- file.path(out,paste(flag,"_CVpredCASFRupperPI95.Rdata",sep=""))
save(CVpredCASFRupperPI95,file = file)
}
##################################################
Extract_CPM_Observed_ASFR_function <- function(asfr_period_hfd,JOY=1936:2014,obs=40,age1=15,age2=44,len=50,full_names=full_names,out="Results/"){
CVpredASFR <- array(NA,dim=c(length(full_names),length(1936:2014),length(age1:age2),length(1895:2050)),dimnames=list(names(full_names),1936:2014,age1:age2,1895:2050))
cohorts <- colnames(asfr_period_to_cohort(CVpredASFR[1,1,,]))
CVpredCASFR <- array(NA,dim=c(length(full_names),length(1936:2014),length(age1:age2),length(cohorts)),dimnames=list(names(full_names),1936:2014,age1:age2,cohorts))
for(joy in JOY){
print(joy)
for(pop in names(full_names)){
print(pop)
ASFR <- asfr_period_hfd[paste(age1:age2),,pop]
if(all(!is.na(ASFR[1,paste((joy-obs+1):joy)]))){
temp <- asfr_period_hfd[paste(age1:age2),paste(JOY),pop]
temp[,1:which(colnames(temp)==joy)] <- NA
temp[,intersect(which(colnames(temp)==joy)+c(len:200),c(1:ncol(temp)))] <- NA
CVpredASFR[pop,paste(joy),rownames(temp),intersect(colnames(temp),paste(1895:2050))] <- as.matrix(temp[,intersect(colnames(temp),paste(1895:2050))])
temp <- asfr_period_to_cohort(temp)
CVpredCASFR[pop,paste(joy),rownames(temp),intersect(colnames(temp),paste(cohorts))] <- as.matrix(temp[,intersect(colnames(temp),paste(cohorts))])
}
}
}
flag <- paste("Forecastlist_RealData","obs",obs,"len",len,sep="_")
file <- file.path(out,paste(flag,"_CVpredASFR.Rdata",sep=""))
save(CVpredASFR,file = file)
file <- file.path(out,paste(flag,"_CVpredCASFR.Rdata",sep=""))
save(CVpredCASFR,file = file)
}
########################################################
Extract_CPM_RealPred_Given_JOY_function <- function(asfr_period_hfd,obs=5,age1=15,age2=44,parameter= c(5),len=50,name="Myrskyla2013",file.head="CVlist",folder="Results/CV/Method18_Myrskyla2013",out="Results/CV"){
Years <- as.numeric(dimnames(asfr_period_hfd)[[2]])
Country <- dimnames(asfr_period_hfd)[[3]]
CPMobj <- list()
for(pop in Country){
joy <- max(Years[!is.na(asfr_period_hfd[1,,pop])])
if(name != "")
label <- ifelse(all(!is.na(parameter)),paste(name,paste(parameter,collapse = "_"),sep="_"),name)
if(name == "")
label <- ifelse(all(!is.na(parameter)),paste(paste(parameter,collapse = "_"),sep="_"),name)
flag <- paste(file.head,label,"obs",obs,"joy",joy,"len",len,sep="_")
file <- file.path(folder,paste(flag,".Rdata",sep=""))
load(file)
print(paste(pop,joy))
CPMobj[[pop]] <- CPMobjlist[[pop]]
}
write_CPMobjlist_to_file(CPMobj,out,header="Forecastlist")
}