Descript 
1 online resource (x, 257 pages) : illustrations, digital ; 24 cm 

text txt rdacontent 

computer c rdamedia 

online resource cr rdacarrier 

text file PDF rda 
Series 
Contributions to statistics, 14311968


Contributions to statistics

Note 
Foreword  Comparison of estimation methods for inverse Weibull distribution (F. G. Akgul, B. Senoglu)  Liutype negative binomial regression (Y. Asar)  Appraisal of performance of three treebased classification methods (H. D. Asfha, B. K. Kilinc)  Highdimensional CLTs for individual Mahalanobis distances (D. Dai, T. Holgersson)  Bootstrap type1 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. O. Akyuz)  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 mconsecutivekoutofn: 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 rankdeficiency of a linear model (B. Schaffrin, K. Snow, X. Fang)  Exact likelihoodbased point and interval estimation for lifetime characteristics of Laplace distribution based on hybrid TypeI and TypeII censored data (F. Su, N. Balakrishnan, X. Zhu)  Statistical inference for twocompartment model parameters with bootstrap method and genetic algorithm (O. Turksen, M. Tez) 

This volume features selected contributions on a variety of topics related to linear statistical inference. The peerreviewed papers from the International Conference on Trends and Perspectives in Linear Statistical Inference (LinStat 2016) held in Istanbul, Turkey, 2225 August 2016, cover topics in both theoretical and applied statistics, such as linear models, highdimensional 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 
Host Item 
Springer eBooks

Subject 
Linear models (Statistics)  Congresses


Mathematical statistics  Congresses


Statistics


Statistical Theory and Methods


Statistics for Business/Economics/Mathematical Finance/Insurance


Statistics for Life Sciences, Medicine, Health Sciences


Statistics and Computing/Statistics Programs

Alt Author 
Tez, Mujgan, editor


von Rosen, Dietrich, editor


SpringerLink (Online service)

Alt Title 
LINSTAT2016 
