Statistical Inference from Stochastic Processes.

Intro -- Contents -- Preface -- Invited Speakers -- Partially specified semimartingale experiments -- Censoring, truncation and filtering in statistical models based on counting processes -- Right censoring and the Kaplan-Meier and Nelson-Alilen estimators. Summary of results -- Partial likelihood: applications, ramifications, generalizations -- Multiple regression with integrated time series -- Analysis of grouped duration data -- Asymptotic theory for weighted least squares estimators in Aalen's additive risk model -- Some applications in statistics of semimartingale weak convergence theorems -- Censoring, martingales and the Cox model -- Composite likelihood methods -- Fixed sample and asymptotic optimality for classes of estimating functions -- Statistical inference from sampled data for stochastic processes -- Optimal properties of SPRT for some stochastic processes -- Estimation theory for the branching process with immigration -- A sequential approach for reducing curved exponential families of stochastic processes to noncurved exponential ones -- Palm distributions of point processes and their applications to statistical inference -- The mathematical structure of error correction models.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.