2025
Mutually exciting point processes for crowdfunding platform dynamics
Djorno A, Crawford F. Mutually exciting point processes for crowdfunding platform dynamics. The Annals Of Applied Statistics 2025, 19: 1931-1947. DOI: 10.1214/25-aoas2051.Peer-Reviewed Original Research
2018
Computational methods for birth‐death processes
Crawford FW, Ho LST, Suchard MA. Computational methods for birth‐death processes. Wiley Interdisciplinary Reviews Computational Statistics 2018, 10 PMID: 29942419, PMCID: PMC6014701, DOI: 10.1002/wics.1423.Peer-Reviewed Original ResearchBirth-death processStatistical inferenceGeneral birth–death processesFinite-time transitionBasic mathematical theoryNon-negative integersContinuous-time Markov chainMaximum likelihood estimationMathematical theoryTheoretical propertiesComputational difficultiesProbability distributionMarkov chainAnalytic expressionsEM algorithmEquilibrium probabilityStatistical workLikelihood estimationSimple caseLinear processRich varietyComputational methodsSimple linear processSummary statisticsInference
2014
Estimation for General Birth-Death Processes
Crawford FW, Minin VN, Suchard MA. Estimation for General Birth-Death Processes. Journal Of The American Statistical Association 2014, 109: 730-747. PMID: 25328261, PMCID: PMC4196218, DOI: 10.1080/01621459.2013.866565.Peer-Reviewed Original ResearchBirth-death processGeneral birth–death processesConditional expectationE-stepEM algorithmLinear birth-death processContinuous-time Markov chainTransition probabilitiesClosed-form solutionLinear modelMaximum likelihood estimatesMaximum likelihood estimationTime-consuming simulationsStatistical inferenceCostly simulationsData augmentation procedureMarkov chainDiscrete timeEfficient computationLikelihood estimatesNumber of particlesFraction representationLaplace transformLikelihood estimationAlgorithm convergence
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply