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IvanWilli/DemoKin: DemoKin estimates kinship distribution by type and age

This is an R package for the demographic analysis of kinship networks using matrix-based models.
It implements methods developed initially by Caswell (2019), and continued in successive papers (like Caswell (2020) or Caswell (2024)) for estimating the number and age distribution of relatives under various demographic assumptions.

• Estimate kin counts and age distributions for various types of relatives
• Support for one-sex and two-sex models
• Time-invariant and time-varying approaches
• Multi-state models incorporating additional variables like parity or education
• Visualization tools for kinship networks

You can install the development version of DemoKin from GitHub:

# install.packages("remotes")
remotes::install_github("IvanWilli/DemoKin")
library(DemoKin)

Here’s a basic example of how to use DemoKin:

# Run a one-sex time-invariant kinship model using Swedish data from 2015
kin_results <- kin(
  p = swe_px[,"2015"],        # Survival probabilities
  f = swe_asfr[,"2015"],      # Fertility rates
  time_invariant = TRUE       # Use time-invariant model
)

# Visualize the expected number of living relatives by age
kin_results$kin_summary %>%
  rename_kin() %>%
  ggplot2::ggplot(ggplot2::aes(age_focal, count_living)) +
  ggplot2::geom_line() +
  ggplot2::facet_wrap(~kin_label, scales = "free_y") +
  ggplot2::labs(
    title = "Expected number of living relatives by age",
    x = "Age of focal individual",
    y = "Number of relatives"
  )

For detailed documentation, please visit the DemoKin website.

The site includes several vignettes demonstrating different types of kinship models:

• One-sex time-invariant kinship model
• One-sex time-varying kinship model
• Two-sex time-invariant kinship model
• Two-sex time-varying kinship model

• One-sex time-invariant multi-state model
• Two-sex time-varying multi-state model

DemoKin has benefited from the work of many people over the years, including:

• Ivan Williams (University of Buenos Aires) leads the technical development of DemoKin with a particular focus on the implementation of the functions in R.

• Diego Alburez-Gutierrez (Max Planck Institute for Demographic Research) coordinates the development of the package.

• Hal Caswell (University of Amsterdam) provided crucial MATLAB code for computing matrix kinship models.

• Xi Song (University of Pennsylvania) contributed the code to estimate time variant kinship models.

• Benjamin Schlüter (University of Toronto) contributed code to implement bereavement analysis by cause of death.

• Joe Butterick (University of Southampton) contributed code to implement time-variant, two-sex multistate kinship models.

• Jason Hilton (University of Southampton) contributed code to implement time-variant, two-sex multistate kinship models.

• Sha Jiang (Max Planck Institute for Demographic Research) helped create and organise the documention for the package, including developing the package’s website.

• Amanda Martins (Max Planck Institute for Demographic Research) developed materials for teaching DemoKin, including a course at the European Doctoral School of Demography.

Williams, Iván; Alburez-Gutierrez, Diego; and the DemoKin team. (2021) DemoKin: An R package to implement demographic matrix kinship models. URL: https://github.com/IvanWilli/DemoKin.

We thank Silvia Leek from the Max Planck Institute for Demographic Research for designing the DemoKin logo. The logo includes elements that have been taken or adapted from this file, originally by Ansunando, CC BY-SA 4.0 via Wikimedia Commons. Sha Jiang provided useful comments for improving the package.

DemoKin is under constant development. If you’re interested in contributing, please get in touch, create an issue, or submit a pull request. We look forward to hearing from you!

This project is licensed under the MIT License - see the LICENSE file for details.

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