hhmR (version 0.0.1)

example_time_series: example_time_series

Description

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.

Usage

data(example_time_series)

Format

A data frame with 90 rows and 4 variables.

County

The county (lower-level geography) that immigrants move to.

Region

The region (higher-level geography) that immigrants move to.

Year

The year during which each wave of immigration occured.

Immigration

The number of immigrants that moved each county in each year.

Examples

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