An Optimum Property of Regular Maximum Likelihood Estimation

Godambe, V. P.

doi:10.1214/aoms/1177705693

Cited by 661 publications

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“…Under usual regularity assumptions, the CML estimator of θ is consistent and asymptotically normally distributed with asymptotic mean θ and covariance matrix given by the inverse of Godambe's (1960) sandwich information matrix (see Zhao and Joe, 2005):…”

Section: Model Estimationmentioning

confidence: 99%

On accommodating spatial dependence in bicycle and pedestrian injury counts by severity level

Narayanamoorthy

Paleti

Bhat

2013

Transportation Research Part B: Methodological

126

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In loving memory of my grandmother N. N. Rugmani AcknowledgmentsFirst and foremost, I must express appreciation to Dr. Chandra Bhat, with whom it has been a pleasure and a privilege to work. I thank him for his insights and advice as also for the stimulus and motivation to dig deep into research. I am grateful to him for showing me how to make sense of mathematical models and for instilling in me the notion that writing should be simple, direct, logical, and tight. His invaluable ideas and the high standards that he sets for himself and his students form the backbone of

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Section: Model Estimationmentioning

confidence: 99%

On accommodating spatial dependence in bicycle and pedestrian injury counts by severity level

Narayanamoorthy

Paleti

Bhat

2013

Transportation Research Part B: Methodological

126

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“…The properties of the general CML estimator may be derived using the theory of estimating equations (see Cox andReid, 2004, Yi et al, 2011). Specifically, under usual regularity assumptions (Molenberghs andVerbeke, 2005, page 191, Xu and, the CML estimator of θ is consistent and asymptotically normal distributed with asymptotic mean θ and covariance matrix given by the inverse of Godambe's (1960) sandwich information matrix (see Zhao and Joe, 2005):…”

Section: The Composite Marginal Likelihood Approachmentioning

confidence: 99%

A latent variable representation of count data models to accommodate spatial and temporal dependence: Application to predicting crash frequency at intersections

Castro

Paleti

Bhat

2012

Transportation Research Part B: Methodological

135

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This paper proposes a reformulation of count models as a special case of generalized orderedresponse models in which a single latent continuous variable is partitioned into mutually exclusive intervals. Using this equivalent latent variable-based generalized ordered response framework for count data models, we are then able to gainfully and efficiently introduce temporal and spatial dependencies through the latent continuous variables. Our formulation also allows handling excess zeros in correlated count data, a phenomenon that is commonly found in

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“…However, we are not aware of a source that collates and presents all of it in generally applicable terms. The extensive statistical literature on EFs is focused primarily on optimality in specific settings [5,6]. In parallel, a large body of econometrics literature, under the guise of the generalized method of moments (GMM) discussed in §4, deals mainly with regression-type models (see [7 -9], ch.…”

Section: Introductionmentioning

confidence: 99%

Estimating functions and the generalized method of moments

Jesus

Chandler

2011

Interface Focus.

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Estimating functions provide a very general framework for statistical inference, and are particularly useful when one is either unable or unwilling to specify a likelihood function. This paper aims to provide an accessible review of estimating function theory that has potential for application to the analysis and modelling of a wide range of complex systems. Assumptions are given in terms that can be checked relatively easily in practice, and some of the more technical derivations are relegated to an online supplement for clarity of exposition. The special case of the generalized method of moments is considered in some detail. The main points are illustrated by considering the problem of inference for a class of stochastic rainfall models based on point processes, with simulations used to demonstrate the performance of the methods.

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An Optimum Property of Regular Maximum Likelihood Estimation

Cited by 661 publications

References 0 publications

On accommodating spatial dependence in bicycle and pedestrian injury counts by severity level

On accommodating spatial dependence in bicycle and pedestrian injury counts by severity level

A latent variable representation of count data models to accommodate spatial and temporal dependence: Application to predicting crash frequency at intersections

Estimating functions and the generalized method of moments

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