Trends and Perspectives in Linear Statistical Inference -

Trends and Perspectives in Linear Statistical Inference

LinStat, Istanbul, August 2016
Buch | Hardcover
X, 257 Seiten
2018 | 1st ed. 2018
Springer International Publishing (Verlag)
978-3-319-73240-4 (ISBN)
128,39 inkl. MwSt

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. 

Müjgan Tez is a professor at the Department of Mathematics of the Marmara University in Istanbul, Turkey. Her research interests include nonlinear models, measurement error of nonlinear models, geometry of statistical models, variance and covariance analysis, mixed models and meta-analysis. Dietrich von Rosen graduated in mathematical statistics at Stockholm University, Sweden and is currently a professor at the Department of Energy and Technology of the Swedish University of Agricultural Sciences. His main research interest is multivariate analysis and its extensions, including repeated measurements analysis and high-dimensional analysis.

Foreword.- Comparison of estimation methods for inverse Weibull distribution (F. G. Akgül, B. Senoglu).- 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. Egrioglu).- 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, I. Batmaz).- Contemporary robust optimal design strategies (T. E. O'Brien).- Alternative approaches for the use of uncertain prior information to overcome the rank-deficiency of a linear model (B. Schaffrin, K. Snow, X. Fang).-  Exact likelihood-based point and interval estimation for lifetime characteristics of Laplace distribution based on hybrid Type-I and Type-II censored data (F. Su, N. Balakrishnan, X. Zhu).- Statistical inference for two-compartment model parameters with bootstrap method and genetic algorithm (Ö. Türksen, M. Tez).

Erscheinungsdatum
Reihe/Serie Contributions to Statistics
Zusatzinfo X, 257 p. 60 illus., 26 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 567 g
Themenwelt Mathematik / Informatik Mathematik Computerprogramme / Computeralgebra
Mathematik / Informatik Mathematik Statistik
Mathematik / Informatik Mathematik Wahrscheinlichkeit / Kombinatorik
Wirtschaft
Schlagworte Estimators • high-dimensional statistical analysis • linear experiments • linear statistical inference • linear statistical models • mixed linear model • Model Selection • multivariate model • prediction and testing • Theoretical and Applied statistics • variance components
ISBN-10 3-319-73240-4 / 3319732404
ISBN-13 978-3-319-73240-4 / 9783319732404
Zustand Neuware
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