Описание: Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. This work treats the basic and important topics in multivariate statistics.
Описание: Suitable for those who needs to communicate complex research results, this title includes four new chapters that cover writing about interactions, writing about event history analysis, writing about multilevel models, and the "Goldilocks principle" for choosing the right size contrast for interpreting results for different variables.
Название: Advances in multivariate statistical analysis ISBN: 9048184398 ISBN-13(EAN): 9789048184392 Издательство: Springer Рейтинг: Цена: 35218.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The death of Professor K. C. Sreedharan Pillai on June 5, 1985 was a heavy loss to many statisticians all around the world. This volume is dedicated to his memory in recog- nition of his many contributions in multivariate statis- tical analysis. It brings together eminent statisticians Working in multivariate analysis from around the world. The research and expository papers cover a cross-section of recent developments in the field. This volume is especially useful to researchers and to those who want to keep abreast of the latest directions in multivariate statistical analysis. I am grateful to the authors from so many different countries and research institutions who contributed to this volume. I wish to express my appreciation to all those who have reviewed the papers. The list of people include Professors T. C. Chang, So-Hsiang Chou, Dipak K. Dey, Peter Hall, Yu-Sheng Hsu, J. D. Knoke, W. J. Krzanowski, Edsel Pena, Bimal K. Sinha, Dennis L. Young, Drs. K. Krishnamoorthy, D. K. Nagar, and Messrs. Alphonse Amey, Chi-Chin Chao and Samuel Ofori-Nyarko. I wish to thank Professors Shanti S. Gupta and James 0. Berger for their keen interest and encouragement. Thanks are also due to Cynthia Patterson for her help and Reidel Publishing Com any for their cooperation in bringing this volume out.
Описание: An accessible guide to the multivariate time series tools used in numerous real-world applications Multivariate Time Series Analysis: With R and Financial Applications is the much anticipated sequel coming from one of the most influential and prominent experts on the topic of time series.
Автор: V.I. Serdobolskii Название: Multivariate Statistical Analysis ISBN: 0792366433 ISBN-13(EAN): 9780792366430 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents a branch of mathematical statistics which intends to construct unimprovable methods of multivariate analysis, multi-parametric estimation, and discriminant and regression analysis. This work is suitable for researchers and graduate students whose work involves statistics and probability, reliability and risk analysis, and econometrics.
Автор: Risto D.H. Heijmans; D.S.G. Pollock; Albert Satorr Название: Innovations in Multivariate Statistical Analysis ISBN: 0792386361 ISBN-13(EAN): 9780792386360 Издательство: Springer Рейтинг: Цена: 29209.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The three decades which have followed the publication of Heinz Neudecker`s seminal paper `Some Theorems on Matrix Differentiation with Special Reference to Kronecker Products` in the Journal of the American Statistical Association (1969) have witnessed the growing influence of matrix analysis in many scientific disciplines.
Автор: Koch Название: Analysis of Multivariate and High-Dimensional Data ISBN: 0521887933 ISBN-13(EAN): 9780521887939 Издательство: Cambridge Academ Рейтинг: Цена: 10613.00 р. Наличие на складе: Поставка под заказ.
Описание: `Big data` poses challenges that require both classical multivariate methods and modern machine-learning techniques. This coherent treatment integrates theory with data analysis, visualisation and interpretation of the analysis. Problems, data sets and MATLAB (R) code complete the package. It is suitable for master`s/graduate students in statistics and working scientists in data-rich disciplines.
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