LabCompass

Daniel Manrique‐Vallier

Mathematics · Indiana University

OpenAlex ORCID
Census and Population EstimationStatistical Methods and Bayesian InferenceBayesian Methods and Mixture ModelsData-Driven Disease SurveillanceHealth and Conflict Studies

Publications

23

Citations

379

Est. group size

—

Recurring co-author estimate

Active years

17

Publishing since 2008

Research summary
AI-generated

Daniel Manrique-Vallier develops statistical methods for estimating the size of populations that are difficult to count directly, such as casualties of armed conflicts or hidden groups in social and medical settings. His work relies on capture-recapture techniques (combining multiple incomplete lists of people) and Bayesian statistics, including methods for handling messy categorical data and generating privacy-preserving synthetic datasets. A recurring application is estimating fatalities from the Peruvian internal armed conflict.

Population size estimationCapture-recapture methodsBayesian statistics and mixture modelsCategorical data editing and synthetic dataConflict casualty estimation

Publication activity peaked around 2018-2019 and has since slowed to roughly one paper every couple of years.

Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026

Publication cadence
Publications per year over the last 10 years — averaging 0.4/year recently
172018: 2 publications182019: 5 publications5192020: 1 publication20212022: 1 publication22232024: 1 publication242526
Recent publications
Publishes in
  • arXiv (Cornell University)×3
  • Biometrics×2
  • Harvard Dataverse×2
  • Journal of the American Statistical Association×1
  • Journal of the Royal Statistical Society Series A (Statistics in Society)×1

This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 11, 2026.

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