Sensitivity Analysis: Matrix Methods in Demography and Ecology

2019/01/01 by Hal Caswell · 1 voice · 3 citations
Social Sciences · Mathematics · #Insurance, Mortality, Demography, Risk Management #COVID-19 epidemiological studies

paper · pdf · doi:10.1007/978-3-030-10534-1

openalex publication_date 2019/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

Abstract

This open access book shows how to use sensitivity analysis in demography, by developing mathematical theory, showing examples of application and presenting new methods for individuals, cohorts, and populations, with applications to humans, other animals, and plants.

Citations

• Comparison of perturbation bounds for the stationary distribution of a Markov chain
• The effect of periodic habitat fluctuations on a nonlinear insect population model
• Nonlinear Demographic Dynamics: Mathematical Models, Statistical Methods, and Biological Experiments
• Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission
• Sensitivity and convergence of uniformly ergodic Markov chains
• The Commutation Matrix: Some Properties and Applications
• Pleiotropy, Natural Selection, and the Evolution of Senescence

Cited by

• Evolutionary–developmental (evo-devo) dynamics of hominin brain size
• Reparations for Black American descendants of persons enslaved in the U.S. and their potential impact on SARS-CoV-2 transmission
• Matrix differential calculus with applications in the multivariate linear model and its diagnostics

Discussions

• FWIW Caswell 2019 doi.org/10.1007/978-... chapter 5 appendix A.5 derives cohort generation time from a discrete-time transition matrix; need to think about implementing/how it generalizes to the ODE c [bsky, 0 points, 0 comments]

Related

• Modeling a demographic problem using the Leslie matrix
• sensobol: an R package to compute variance-based sensitivity indices
• The Future of Sensitivity Analysis: An essential discipline for systems modeling and policy support
• Toward an Ecological Demography
• Statistical sensitiveness for science