Efficiency of estimators for partially specified filtered models

DOI10.1016/0304-4149(90)90101-WzbMath0719.62050MaRDI QIDQ2640277

Prescilla E. Greenwood, Wolfgang Wefelmeyer

Publication date: 1990

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

zbMATH Keywords

asymptotic normalityDoob-Meyer decompositionproportional hazards modelcounting processescompensatorefficiency of estimatorssmooth functionalAalen's additive risk modelregular estimatesfiltered modelsCox estimatorHájek-type convolution theorempartially specified likelihoodpredictable intensity processvector process of covariates

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Non-Markovian processes: estimation (62M09)

Related Items (12)

An efficient estimator for the expectation of a bounded function under the residual distribution of an autoregressive process ⋮ On local odds and hazard rate models in survival analysis ⋮ Nonparametric estimators for Markov step processes ⋮ Efficient estimation in a nonlinear counting-process regression model ⋮ Adaptive estimators for parameters of the autoregression function of a Markov chain ⋮ Aalen's linear model for doubly censored data ⋮ Quasi-likelihood models and optimal inference ⋮ Efficiency of the maximum partial likelihood estimator for nested case control sampling ⋮ Information and asymptotic efficiency of the case-cohort sampling design in Cox's regression model ⋮ Efficient Estimation of Fixed and Time‐varying Covariate Effects in Multiplicative Intensity Models ⋮ Asymptotically optimal estimation in misspecified time series models ⋮ Information bounds for Gibbs samplers

Cites Work

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