asymptotic statistics cambridge series in statistical and probabilistic mathematics

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Asymptotic Statistics

Author : A. W. van der Vaart
ISBN : 0521784506
Genre : Mathematics
File Size : 58. 4 MB
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A mathematically rigorous, practical introduction presenting standard topics plus research.

Advances In Directional And Linear Statistics

Author : Martin T. Wells
ISBN : 3790826286
Genre : Mathematics
File Size : 73. 8 MB
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The present volume consists of papers written by students, colleagues and collaborators of Sreenivasa Rao Jammalamadaka from various countries, and covers a variety of research topics which he enjoys and contributed immensely to.

From Finite Sample To Asymptotic Methods In Statistics

Author : Pranab K. Sen
ISBN : 9780521877220
Genre : Mathematics
File Size : 71. 89 MB
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A broad view of exact statistical inference and the development of asymptotic statistical inference.

Applied Asymptotics

Author : A. R. Brazzale
ISBN : 0521847036
Genre : Business & Economics
File Size : 52. 76 MB
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First practical treatment of small-sample asymptotics, enabling practitioners to apply new methods with confidence.

Empirical Processes In M Estimation

Author : Sara A. van de Geer
ISBN : 0521123259
Genre : Mathematics
File Size : 62. 25 MB
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The theory of empirical processes provides valuable tools for the development of asymptotic theory in (nonparametric) statistical models, and makes it possible to give a unified treatment of various models. This book reveals the relation between the asymptotic behavior of M-estimators and the complexity of parameter space, using entropy as a measure of complexity, presenting tools and methods to analyze nonparametric, and in some cases, semiparametric methods. Graduate students and professionals in statistics, as well as those interested in applications, e.g. to econometrics, medical statistics, etc., will welcome this treatment.

Journal Of Statistical Planning And Inference

Author : Elsevier Science Publishers (Amsterdam, Países Bajos)
ISBN : 03783758
Genre :
File Size : 53. 1 MB
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Elements Of Distribution Theory

Author : Thomas A. Severini
ISBN : 052184472X
Genre : Business & Economics
File Size : 32. 59 MB
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This detailed introduction to distribution theory uses no measure theory, making it suitable for students in statistics and econometrics as well as for researchers who use statistical methods. Good backgrounds in calculus and linear algebra are important and a course in elementary mathematical analysis is useful, but not required. An appendix gives a detailed summary of the mathematical definitions and results that are used in the book. Topics covered range from the basic distribution and density functions, expectation, conditioning, characteristic functions, cumulants, convergence in distribution and the central limit theorem to more advanced concepts such as exchangeability, models with a group structure, asymptotic approximations to integrals, orthogonal polynomials and saddlepoint approximations. The emphasis is on topics useful in understanding statistical methodology; thus, parametric statistical models and the distribution theory associated with the normal distribution are covered comprehensively.

Economic Computation And Economic Cybernetics Studies And Research

Author :
ISBN : STANFORD:36105123824893
Genre : Business & Economics
File Size : 85. 71 MB
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On Goodness Of Fit Tests Of Semiparametric Models

Author : Bo Li
ISBN : UCAL:C3507631
Genre :
File Size : 48. 3 MB
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Comprehensive model adequacy checking procedures are discussed for general parametric and semiparametric model specifications, with illustration in a variety of examples containing assumptions on dependence structures, density shapes, functional forms and other model features. We use the efficient score processes developed by Bickel, Ritov and Stoker (2006) as building blocks, from which many omnibus tests can be constructed. This set of omnibus tests include Class I tests with decreasing power along high frequencies, and Class II tests with approximately equal power on limited frequencies. We also give a unified view of a group of asymptotically distribution free tests from the score perspective. This set of tests is essentially derived from a family of inefficient scores, enabling the limit Gaussian processes to have nice variance-covariance structure. Additionally, we propose data-driven tests in the score and spectral domains. Either model selection rules or thresholding methods are invoked to choose the scores or spectra on which to focus. Finally, we consider aggregating different types of tests, primarily combining one Class I test and one Class II test, in the hope of achieving a balance between the two classes. Numerical experiments confirm that both Class I and Class II tests have their own strong and weak aspects, and the aggregated procedures demonstrate a balanced and stable performance; although signal strength (of departures) is a fundamental limiting factor of all such procedures. In summary, a statistical model is warranted only when it passes various diagnostic checks with different but complementary strengths.

A Generalized Self Consistency Approach To Semiparametric Survival Models

Author : Szu-Ching Tseng
ISBN : UCAL:X78010
Genre :
File Size : 42. 42 MB
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