Fake migration dataset used to demonstrate the functionality of the tshm function in the hhmR package. It contains the information on the number of people who have immigrated a series of fictional geographies over the years 2011 to 2015. The geographies themselves have a hierarchical structure, with each county existing within a smaller subset of regions.
data(example_time_series)A data frame with 90 rows and 4 variables.
The county (lower-level geography) that immigrants move to.
The region (higher-level geography) that immigrants move to.
The year during which each wave of immigration occured.
The number of immigrants that moved each county in each year.
library(dplyr)
library(tidyr)
# Define names of fake counties
fake_counties = c("Greenridge","Windermoor","Bramblewood","Silverlake",
"Thornbury","Maplewood","Hawthorne","Pinehurst",
"Riverton","Meadowbrook","Fairhaven","Oakdale","Stonebridge",
"Brookfield","Ashford","Glenville","Sunnyvale","Westfield")
# Create dataframe of fake migration data
set.seed(1234)
example_time_series = data.frame(region = c(rep("North",3),rep("Midlands",5),
rep("South West",4),rep("South East",6)),
county = fake_counties,
year_2011 = sample(1:10000,length(fake_counties)),
year_2012 = sample(1:10000,length(fake_counties)),
year_2013 = sample(1:10000,length(fake_counties)),
year_2014 = sample(1:10000,length(fake_counties)),
year_2015 = sample(1:10000,length(fake_counties))) %>%
setNames(c("Region","County",2011:2015)) %>%
pivot_longer(cols = `2011`:`2015`,
names_to = "Year",
values_to = "Immigration") %>%
mutate(Year = as.numeric(Year))
example_time_series[sample(1:(length(fake_counties)*5),5),"Immigration"] = NA