35 lines
1.2 KiB
R
35 lines
1.2 KiB
R
library(tidyverse)
|
|
library(bayesPop)
|
|
library(bayesMig)
|
|
|
|
|
|
DAT <- read_tsv(us.mig.file)
|
|
DAT[,2] %>% t
|
|
sum(DAT$`2001`)
|
|
|
|
# Toy simulation for US states
|
|
dir.create("Output")
|
|
sim.dir <- "./Output"
|
|
us.mig.file <- file.path(find.package("bayesMig"), "extdata", "USmigrates.txt")
|
|
m <- run.mig.mcmc(nr.chains = 2, iter = 100000, thin = 1, my.mig.file = us.mig.file,
|
|
output.dir = sim.dir, present.year = 2017, annual = TRUE)
|
|
pred <- mig.predict(sim.dir = sim.dir, burnin = 5, end.year = 2050)
|
|
mig.trajectories.plot(pred, "Wyoming", pi = 80, ylim = c(-0.03, 0.03))
|
|
|
|
load("./Output/bayesMig.mcmc.meta.rda")
|
|
#############
|
|
#subnat example
|
|
data.dir <- "./extdata"
|
|
dir.create("Pop_Output")
|
|
sim.dir <- "./Pop_Output"
|
|
dir.create("Output")
|
|
example(pop.predict.subnat)
|
|
read_tsv(file.path(data.dir, "CANlocations.txt"))
|
|
pred <- pop.predict.subnat(output.dir = sim.dir, locations = file.path(data.dir, "CANlocations.txt"),
|
|
inputs = list(popM = file.path(data.dir, "CANpopM.txt"),popF = file.path(data.dir, "CANpopF.txt")),
|
|
verbose = TRUE)
|
|
pop.pyramid(pred, "Ontario")
|
|
?pop.pyramid
|
|
summary(pred)
|
|
write.pop.trajectories(pred)
|
|
load("Pop_Output/predictions/prediction.rda") |