Estimating Functions

'The book is recommended as a good survey for every researcher with interest in the theory and applications of estimating functions.' Short Book Reviews

• PART 1: OVERVIEW: V.P. Godambe & B.K. Kale: Estimating functions: an overview; PART 2: BIOSTATISTICS: I.-Shou Chang & Chao A. Hsiung: Applications of estimating function theory to replicates of generalized proportional hazards models; C.B. Dean: Estimating equations for mixed Poisson models; Kung-Lee Liang & Xin-Hua Liu: Estimating equations in generalized linear models with measurement error; C.J. Lloyd & P. Yip: A unification of inference from capture-recapture studies through martingale estimating functions; T. Yanagimoto & E. Yamamoto: The role of unbiasedness in estimating equations; L.P. Zhao & R.L. Prentice: Use of a quadratic exponential model to generate estimating equations for means, variances, and covariances; PART 3: STOCHASTIC PROCESSES: I.V. Basawa: Generalized score tests for composite hypotheses; A.F. Desmond: Quasi-likelihood stochastic processes and optimal estimating functions; P.E. Greenwood & W. Wefelmeyer: On optimal estimating functions for partially specified counting process models; C.C. Heyde & Y.-X. Lin: Approximate confidence zones in an estimating function context; J.E. Hutton, O.T. Ogunyemi & P.I. Nelson: Simplified and two-stage quasi-likelihood estimators; A. Thavaneswaran: Tests based on an optimal estimate; PART 4: SURVEY SAMPLING: M. Ghosh: Estimating functions in survey sampling: a review; V.P. Godambe: Confidence intervals for quantiles; H. Mantel: Making use of a regression model for inferences about a finite population mean; K. Vijayan: Estimating functions in survey sampling: estimation of superpopulation regression parameters; PART 5: THEORY (Foundations): V.P. Bhapkar: Sufficiency, ancillarity, and information in estimating functions; S.R. Chamberlin & D.A. Sprott: Inferential estimation, likelihood, and maximum likelihood linear estimating functions; C.G. Small & D.L. McLeish: Geometrical aspects of efficiency criteria for spaces of estimating functions; PART 6: THEORY (General Methods): H. Ferguson, N. Reid & D.R. Cox: Estimating equations from modified profile likelihood; S. Lele: Resampling using estimating equations; B.G. Lindsay & P. Basak: On using bivariate moment equations in mixed normal problems; Y. Ritov: Estimating funtions in semi-parametric models.