Books in the Contributions to Statistics series

This book covers methods for spatial statistical analysis suitable for modeling spatial information in support of decision systems. Includes data mining, point processes analysis, nearest neighbor statistics and cluster detection, Fuzzy Regression and more.

This book presents the latest findings on statistical inference in multivariate, multilinear and mixed linear models, providing a holistic presentation of the subject. It contains pioneering and carefully selected review contributions by experts in the field and guides the reader through topics related to estimation and testing of multivariate and mixed linear model parameters. Starting with the theory of multivariate distributions, covering identification and testing of covariance structures and means under various multivariate models, it goes on to discuss estimation in mixed linear models and their transformations.The results presented originate from the work of the research group Multivariate and Mixed Linear Models and their meetings held at the Mathematical Research and Conference Center in B¿dlewo, Poland, over the last 10 years. Featuring an extensive bibliography of related publications, the book is intended for PhD students and researchers in modern statistical science who are interested in multivariate and mixed linear models.

In turn, the last three parts are dedicated to applied topics and include papers on time series analysis in the earth sciences, energy time series forecasting, and time series analysis and prediction in other real-world problems.

This book provides an overview of the latest developments in the field of risk analysis (RA).

This book presents selected peer-reviewed contributions from the International Work-Conference on Time Series, ITISE 2017, held in Granada, Spain, September 18-20, 2017. It discusses topics in time series analysis and forecasting, including advanced mathematical methodology, computational intelligence methods for time series, dimensionality reduction and similarity measures, econometric models, energy time series forecasting, forecasting in real problems, online learning in time series as well as high-dimensional and complex/big data time series.The series of ITISE conferences provides a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing computer science, mathematics, statistics and econometrics.

This volume conveys some of the surprises, puzzles and success stories in high-dimensional and complex data analysis and related fields. Examples include epigenomic data, genomic data, proteomic data, high-resolution image data, high-frequency financial data, functional and longitudinal data, and network data.

This volume presents selected peer-reviewed contributions from The International Work-Conference on Time Series, ITISE 2015, held in Granada, Spain, July 1-3, 2015. It discusses topics in time series analysis and forecasting, advanced methods and online learning in time series, high-dimensional and complex/big data time series as well as forecasting in real problems.The International Work-Conferences on Time Series (ITISE) provide a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing the disciplines of computer science, mathematics, statistics and econometrics.

This book collects several contributions, written both by statisticians and medical doctors, which focus on the identification of new diagnostic, therapeutic and organizational strategies in order to improve the occurrence of clinical outcomes for Acute Coronary Syndromes (ACS) patients.

This volume features selected, refereed papers on various aspects of statistics, matrix theory and its applications to statistics, as well as related numerical linear algebra topics and numerical solution methods, which are relevant for problems arising in statistics and in big data.

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.

This book presents selected peer-reviewed contributions from the International Work-Conference on Time Series, ITISE 2017, held in Granada, Spain, September 18-20, 2017. It discusses topics in time series analysis and forecasting, including advanced mathematical methodology, computational intelligence methods for time series, dimensionality reduction and similarity measures, econometric models, energy time series forecasting, forecasting in real problems, online learning in time series as well as high-dimensional and complex/big data time series.The series of ITISE conferences provides a forum for scientists, engineers, educators and students to discuss the latest ideas and implementations in the foundations, theory, models and applications in the field of time series analysis and forecasting. It focuses on interdisciplinary and multidisciplinary research encompassing computer science, mathematics, statistics and econometrics.

it deals with some hot topics in sampling theory, such as calibration, quantile-regression and multiple frame surveys and with innovative methodologies in important topics of both sampling theory and applications.

One of the main applications of statistical smoothing techniques is nonparametric regression. Smoothing techniques in regression as well as other statistical methods are increasingly applied in biosciences and economics. Introduced are new developments in scatterplot smoothing and applications in statistical modelling.

The failure of standard multivariate statistics to analyze such functional data has led the statistical community to develop appropriate statistical methodologies, called Functional Data Analysis (FDA).

This book presents a collection of statistical methods and procedures to assess data coming from educational systems.

This volume collects latest methodological and applied contributions on functional, high-dimensional and other complex data, related statistical models and tools as well as on operator-based statistics.

The numerous applications (micro-arrays, paleo- ecological data, radar waveforms, spectrometric curves, speech recognition, continuous time series, 3-D images, etc.) in various fields (biology, econometrics, environmetrics, the food industry, medical sciences, paper industry, etc.) make researching this statistical topic very worthwhile.

Statisticians and experimentalists will find the latest trends in optimal experimental design research. Some papers are pioneering contributions, leading to new open research problems. It is a colection of peer reviewed papers.

This book presents a collection of statistical methods and procedures to assess data coming from educational systems.

The next four meetings were in 1990 (St Kyrik monastery, Bulgaria), 1992 (Petrodvorets, St Petersburg, Russia), 1995 (Spetses, Greece) and 1998 (Marseilles, France). It is a tradition of these meetings to provide low cost accommodation, low fees and financial support for the travel of young and Eastern participants.

The numerous applications (micro-arrays, paleo- ecological data, radar waveforms, spectrometric curves, speech recognition, continuous time series, 3-D images, etc.) in various fields (biology, econometrics, environmetrics, the food industry, medical sciences, paper industry, etc.) make researching this statistical topic very worthwhile.

This volume contains the proceedings of the 8th Workshop on Model-Oriented Design and Analysis. It offers leading and pioneering work on optimal experimental designs, both from a mathematical/statistical point of view and with regard to real applications.

In the last ten years, there has been increasing interest and activity in the general area of partially linear regression smoothing in statistics.

The coverage of the material falls squarely into the following categories: (a) Survival analysis and multivariate survival analysis, (b) Time series and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling.

This book collects several contributions, written both by statisticians and medical doctors, which focus on the identification of new diagnostic, therapeutic and organizational strategies in order to improve the occurrence of clinical outcomes for Acute Coronary Syndromes (ACS) patients.

The coverage of the material falls squarely into the following categories: (a) Survival analysis and multivariate survival analysis, (b) Time series and longitudinal data analysis, (c) Statistical model development and (d) Applied statistical modelling.

This volume is the proceedings of the 4th International Workshop on Model-Oriented Data Analysis. The editors are also grateful to Intracom (Greece), the Ionian Bank and the Procter & Gamble Company (USA) for their generous support.

At the same time, the advent of computers has facilitated the use of modern statistics in all branches of science, making statistics even more interdisciplinary than in the past;