Une pure merveille !
Un roman d'une grande beauté, drôle, fin, extrêmement lumineux sur des sujets difficiles : la perte de
l'être aimé, la dureté de la vie et la tristesse qu'on barricade parfois... Elise franco-japonaise,
orpheline de sa maman veut poser LA question à son père et elle en trouvera le courage au fil des pages,
grâce au retour de sa grand-mère du japon, de sa rencontre avec son extravagante amie Stella..
Ensemble il ne diront plus Sayonara mais Mata Ne !
The theory of empirical processes provides valuable tools for the development of asymptotic theory in (non-parametric) statistical models, and possibly...
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Livré chez vous entre le 5 octobre et le 19 octobre
En librairie
Résumé
The theory of empirical processes provides valuable tools for the development of asymptotic theory in (non-parametric) statistical models, and possibly the unified treatment of a number of them. This book reveals the relation between the asymptotic behaviour of M-estimators and the complexity of parameter space. Virtually all results are proved using only elementary ideas developed within the book; there is minimal recourse to abstract theoretical results. To make the results concrete, a detailed treatment is presented for two important examples of M-estimation, namely maximum likelihood and least squares. The theory also covers estimation methods using penalties and sieves.
Many illustrative examples are given, including the Grenander estimator, estimation of functions of bounded variation, smoothing splines, partially linear models, mixture models and image analysis.
Graduate students and professionals in statistics, as well as those with an interest in applications to such areas as econometrics, medical statistics, etc., will welcome this treatment.
Sommaire
Notation and Definitions
Uniform Laws of Large Numbers
First Applications: Consistency
Increments of Empirical Processes
Central Limit Theorems
Rates of Convergence for Maximum Likelihood Estimators