fix in time index for imputation

ChangeLog

@@ -4,6 +4,8 @@ Default for par.names and par.names.cs in e0.raftery.diag changed to all paramet
 
 Fixed bug in e0.joint.plot for annual prediction object.
 
+Fixed bug in setting time index when imputation is present in e0.predict.subnat().
+
 5.2-0 (09/15/2023)
 -----
 Annual subnational projections are now possible, via the argument "annual"

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: bayesLife
 Type: Package
 Title: Bayesian Projection of Life Expectancy
-Version: 5.2-0.9002
-Date: 2023-12-22
+Version: 5.2-0.9003
+Date: 2024-02-02
 Author: Hana Sevcikova, Adrian Raftery, Jennifer Chunn 
 Maintainer: Hana Sevcikova <[email protected]>
 Description: Making probabilistic projections of life expectancy for all countries of the world, using a Bayesian hierarchical model <doi:10.1007/s13524-012-0193-x>. Subnational projections are also supported.

R/project_subnat.R

@@ -153,7 +153,7 @@ e0.predict.subnat <- function(countries, my.e0.file, sim.dir=file.path(getwd(),
         PIs_cqp <- array(NA, c(nr.reg, length(quantiles.to.keep), nrow(wtrajs)),
                      dimnames=list(meta$regions$country_code, dimnames(wpred$quantiles)[[2]], dimnames(wtrajs)[[1]]))
         mean_sd <- array(NA, c(nr.reg, 2, nrow(wtrajs)))
-        #meta$Tc.index <- .get.Tcindex(meta$e0.matrix, cnames = meta$regions$country_name)
+        meta$Tc.index <- .get.Tcindex(meta$e0.matrix, cnames = meta$regions$country_name)
         country.char <- as.character(country.obj$code)
         e0reconstructed <- meta$e0.matrix
 
@@ -171,7 +171,7 @@ e0.predict.subnat <- function(countries, my.e0.file, sim.dir=file.path(getwd(),
                 widx <- which(rownames(wtrajs.all) %in% names(rege0[i]))
                 c.first <- rep(do.call(paste0("compute.alpha.", method), list(rege0[i], wtrajs.all[widx,])), 
                                nr.traj) # set of initial scales
-                meta$Tc.index[region] <- i
+                meta$Tc.index[[region]] <- meta$Tc.index[[region]][meta$Tc.index[[region]] <= i]
                 imptraj <- matrix(NA, nrow = length(rege0) - i, ncol = nr.traj) # trajectory matrix for imputation
                 for(tr in 1:nr.traj) { # iterate over trajectories
                     imp.time <- i:(length(rege0)-1)