Trends and Perspectives in Linear Statistical Inference : LinStat, Istanbul, August 2016. 1st ed. 2018

種類:

電子ブック

責任表示:

edited by Müjgan Tez, Dietrich von Rosen

出版情報:

Cham : Springer International Publishing : Imprint: Springer, 2018

著者名:

• Tez, Müjgan.
• von Rosen, Dietrich.
• SpringerLink (Online service)

シリーズ名:

Contributions to Statistics ;

ISBN:

9783319732411 [3319732412]    

注記:

Foreword -- Comparison of estimation methods for inverse Weibull distribution (F. G. Akgül, B. Şenoğlu) -- Liu-type negative binomial regression (Y. Asar) -- Appraisal of performance of three tree-based classification methods (H. D. Asfha, B. K. Kilinc) -- High-dimensional CLTs for individual Mahalanobis distances (D. Dai, T. Holgersson) -- Bootstrap type-1 fuzzy functions approach for time series forecasting (A. Z. Dalar, E. Eğrioğlu) -- A weighted ensemble learning by SVM for longitudinal data: Turkish bank bankruptcy (B. E. Erdogan, S. Ö. Akyüz) -- The complementary exponential phase type distribution (S. Eryilmaz) -- Best linear unbiased prediction: Some properties of linear prediction sufficiency in the linear model (J. Isotalo, A. Markiewicz, S. Puntanen) -- A note on circular m-consecutive-k-out-of-n: F Systems (C. Kan) -- A categorical principal component regression on computer assisted instruction in probability domain (T. Kapucu, O. Ilk, İ. Batmaz) -- Contemporary robust optimal design strategies (T
This volume features selected contributions on a variety of topics related to linear statistical inference. The peer-reviewed papers from the International Conference on Trends and Perspectives in Linear Statistical Inference (LinStat 2016) held in Istanbul, Turkey, 22-25 August 2016, cover topics in both theoretical and applied statistics, such as linear models, high-dimensional statistics, computational statistics, the design of experiments, and multivariate analysis. The book is intended for statisticians, Ph.D. students, and professionals who are interested in statistical inference. .

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