02959 am 2200673 n 450 991058880020332120240109202926.02-7297-1144-910.4000/books.pul.42277(CKB)4100000012892264(FrMaCLE)OB-pul-42277(oapen)https://directory.doabooks.org/handle/20.500.12854/91947(PPN)264714229(EXLCZ)99410000001289226420220829j|||||||| ||| 0freuu||||||m||||txtrdacontentcrdamediacrrdacarrierAndré Gide & Paul-Albert Laurens Correspondance 1891-1934 /André Gide, Paul-Albert LaurensLyon Presses universitaires de Lyon20221 online resource (236 p.)André Gide - Textes et correspondances2-7297-0894-4 Composée de 130 lettres échangées entre 1891 et 1934, cette correspondance retrace l’histoire d’une amitié de jeunesse prolongée dans l’âge mûr : celle de l’écrivain André Gide et du peintre Paul-Albert Laurens (1870-1934), fils du célèbre peintre d’histoire Jean-Paul Laurens. Au cours de leur voyage en Afrique du Nord en 1893-1894, épisode décisif longuement évoqué dans Si le grain ne meurt, et auquel les lettres ici rassemblées apportent quantité d’éclairages inédits, Laurens et Gide partagent leurs découvertes touristiques et sexuelles et nouent une relation fraternelle, au point d’en faire une des plus durables et profondes que Gide ait connues. Cette amitié est aussi un réseau : fils unique et bientôt orphelin, Gide a trouvé, avec Paul-Albert Laurens, son frère Pierre et leurs parents, une seconde famille ; il a rencontré enfin, avec eux, un milieu d’artistes et d’écrivains qu’il n’a plus quitté.Andrà Gide & Paul-Albert LaurensLiterature (General)littérature françaiselittératurelittérature épistolaireXXe sièclepeintreécrivainlettrelittérature françaiselittératurelittérature épistolaireXXe sièclepeintreécrivainlettreLiterature (General)littérature françaiselittératurelittérature épistolaireXXe sièclepeintreécrivainlettreGide André385265Laurens Paul-Albert1329841Masson Pierre174491Wittmann Jean-Michel313088FR-FrMaCLEBOOK9910588800203321André Gide & Paul-Albert Laurens3039638UNINA05448nam 22006494a 450 991083013370332120230828213320.01-280-44838-597866104483880-470-00967-50-470-00966-7(CKB)1000000000355635(EBL)257544(OCoLC)475973641(SSID)ssj0000212012(PQKBManifestationID)11174860(PQKBTitleCode)TC0000212012(PQKBWorkID)10136427(PQKB)11634071(MiAaPQ)EBC257544(EXLCZ)99100000000035563520051202d2006 uy 0engur|n|---|||||txtccrNonparametric regression methods for longitudinal data analysis[electronic resource] [mixed-effects modeling approaches] /Hulin Wu, Jin-Ting ZhangHoboken, N.J. Wiley-Intersciencec20061 online resource (401 p.)Wiley series in probability and statisticsSubtitle from cover.0-471-48350-8 Includes bibliographical references (p. 347-361) and index.Nonparametric Regression Methods for Longitudinal Data Analysis; Preface; Contents; Acronyms; 1 Introduction; 1.1 Motivating Longitudinal Data Examples; 1.1.1 Progesterone Data; 1.1.2 ACTG 388 Data; 1.1.3 MACS Data; 1.2 Mixed-Effects Modeling: from Parametric to Nonparametric; 1.2.1 Parametric Mixed-Effects Models; 1.2.2 Nonparametric Regression and Smoothing; 1.2.3 Nonparametric Mixed-Effects Models; 1.3 Scope of the Book; 1.3.1 Building Blocks of the NPME Models; 1.3.2 Fundamental Development of the NPME Models; 1.3.3 Further Extensions of the NPME Models1.4 Implementation of Methodologies1.5 Options for Reading This Book; 1.6 Bibliographical Notes; 2 Parametric Mixed-Effects Models; 2.1 Introduction; 2.2 Linear Mixed-Effects Model; 2.2.1 Model Specification; 2.2.2 Estimation of Fixed and Random-Effects; 2.2.3 Bayesian Interpretation; 2.2.4 Estimation of Variance Components; 2.2.5 The EM-Algorithms; 2.3 Nonlinear Mixed-Effects Model; 2.3.1 Model Specification; 2.3.2 Two-Stage Method; 2.3.3 First-Order Linearization Method; 2.3.4 Conditional First-Order Linearization Method; 2.4 Generalized Mixed-Effects Model2.4.1 Generalized Linear Mixed-Effects Model2.4.2 Examples of GLME Model; 2.4.3 Generalized Nonlinear Mixed-Effects Model; 2.5 Summary and Bibliographical Notes; 2.6 Appendix: Proofs; 3 Nonparametric Regression Smoothers; 3.1 Introduction; 3.2 Local Polynomial Kernel Smoother; 3.2.1 General Degree LPK Smoother; 3.2.2 Local Constant and Linear Smoothers; 3.2.3 Kernel Function; 3.2.4 Bandwidth Selection; 3.2.5 An Illustrative Example; 3.3 Regression Splines; 3.3.1 Truncated Power Basis; 3.3.2 Regression Spline Smoother; 3.3.3 Selection of Number and Location of Knots3.3.4 General Basis-Based Smoother3.4 Smoothing Splines; 3.4.1 Cubic Smoothing Splines; 3.4.2 General Degree Smoothing Splines; 3.4.3 Connection between a Smoothing Spline and a LME Model; 3.4.4 Connection between a Smoothing Spline and a State-Space Model; 3.4.5 Choice of Smoothing Parameters; 3.5 Penalized Splines; 3.5.1 Penalized Spline Smoother; 3.5.2 Connection between a Penalized Spline and a LME Model; 3.5.3 Choice of the Knots and Smoothing Parameter Selection; 3.5.4 Extension; 3.6 Linear Smoother; 3.7 Methods for Smoothing Parameter Selection; 3.7.1 Goodness of Fit3.7.2 Model Complexity3.7.3 Cross-Validation; 3.7.4 Generalized Cross-Validation; 3.7.5 Generalized Maximum Likelihood; 3.7.6 Akaike Information Criterion; 3.7.7 Bayesian Information Criterion; 3.8 Summary and Bibliographical Notes; 4 Local Polynomial Methods; 4.1 Introduction; 4.2 Nonparametric Population Mean Model; 4.2.1 Naive Local Polynomial Kernel Method; 4.2.2 Local Polynomial Kernel GEE Method; 4.2.3 Fan-Zhang 's Two-step Method; 4.3 Nonparametric Mixed-Effects Model; 4.4 Local Polynomial Mixed-Effects Modeling; 4.4.1 Local Polynomial Approximation; 4.4.2 Local Likelihood Approach4.4.3 Local Marginal Likelihood EstimationIncorporates mixed-effects modeling techniques for more powerful and efficient methodsThis book presents current and effective nonparametric regression techniques for longitudinal data analysis and systematically investigates the incorporation of mixed-effects modeling techniques into various nonparametric regression models. The authors emphasize modeling ideas and inference methodologies, although some theoretical results for the justification of the proposed methods are presented.With its logical structure and organization, beginning with basic principles, the text develops tWiley series in probability and statistics.Nonparametric statisticsLongitudinal methodMathematical modelsNonparametric statistics.Longitudinal methodMathematical models.519.5/4519.54Wu Hulin1653704Zhang Jin-Ting1964-1689680MiAaPQMiAaPQMiAaPQBOOK9910830133703321Nonparametric regression methods for longitudinal data analysis4064913UNINA