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Found 96 from your keywords: subject="Statistical"
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Landscape Ecology in Theory and Practice: Pattern and Process
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Monica G. TurnerRobert H. Gardner

This work provides in-depth analysis of the origins of landscape ecology and its close alignment with the understanding of scale, the causes of landscape pattern, and the interactions of spatial pattern with a variety of ecological processes. The text covers the quantitative approaches that are applied widely in landscape studies, with emphasis on their appropriate use and interpretation. Th…

Edition
-
ISBN/ISSN
978-1-4939-2794-4
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-
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-
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-
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cover
Modern Methodology and Applications in Spatial-Temporal Modeling
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PETERS, Gareth WilliamMATASUI, Tomoko

This book provides a modern introductory tutorial on specialized methodological and applied aspects of spatial and temporal modeling. The areas covered involve a range of topics which reflect the diversity of this domain of research across a number of quantitative disciplines. For instance, the first chapter deals with non-parametric Bayesian inference via a recently developed framework known a…

Edition
1
ISBN/ISSN
978-4-431-55338-0
Collation
XV
Series Title
SpringerBriefs in Statistics
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-
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Modern Nonparametric, Robust and Multivariate Methods
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NORDHAUSEN, KlausTASKINEN, Sara

Written by leading experts in the field, this edited volume brings together the latest findings in the area of nonparametric, robust and multivariate statistical methods. The individual contributions cover a wide variety of topics ranging from univariate nonparametric methods to robust methods for complex data structures. Some examples from statistical signal processing are also given. The volu…

Edition
1
ISBN/ISSN
978-3-319-22403-9
Collation
xx, 506
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-
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-
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cover
Estimation and Testing Under Sparsity École d'Été de Probabilités de Sai…
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GEER, Sara van de

Taking the Lasso method as its starting point, this book describes the main ingredients needed to study general loss functions and sparsity-inducing regularizers. It also provides a semi-parametric approach to establishing confidence intervals and tests. Sparsity-inducing methods have proven to be very useful in the analysis of high-dimensional data. Examples include the Lasso and group Lasso m…

Edition
-
ISBN/ISSN
978-3-319-32774-7
Collation
XIII, 274
Series Title
-
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-
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cover
Estimation and Inferential Statistics
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SAHU, Pradip KumarPAL, Santi RanjanDAS, Ajit Kumar

This book focuses on the meaning of statistical inference and estimation. Statistical inference is concerned with the problems of estimation of population parameters and testing hypotheses. Primarily aimed at undergraduate and postgraduate students of statistics, the book is also useful to professionals and researchers in statistical, medical, social and other disciplines. It discusses current …

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-
ISBN/ISSN
978-81-322-2514-0
Collation
23 b/w illustrations
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-
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-
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cover
Essentials of Stochastic Processes
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DURRETT, Richard

Building upon the previous editions, this textbook is a first course in stochastic processes taken by undergraduate and graduate students (MS and PhD students from math, statistics, economics, computer science, engineering, and finance departments) who have had a course in probability theory. It covers Markov chains in discrete and continuous time, Poisson processes, renewal processes, martinga…

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-
ISBN/ISSN
978-3-319-45614-0
Collation
26 b/w illustrations
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-
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-
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cover
Computational modeling of neural activities for statistical inference
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ANTONIO KOLOSSA

This authored monograph supplies empirical evidence for the Bayesian brain hypothesis by modeling event-related potentials (ERP) of the human electroencephalogram (EEG) during successive trials in cognitive tasks. Bayesian model selection is then used to choose the model which best explains the ERP amplitude fluctuations.

Edition
-
ISBN/ISSN
9783319812434
Collation
-
Series Title
-
Call Number
519.542
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cover
Adaptive Regression for Modeling Nonlinear Relationships
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KNAFI, George J.DING, Kai

This book presents methods for investigating whether relationships are linear or nonlinear and for adaptively fitting appropriate models when they are nonlinear. Data analysts will learn how to incorporate nonlinearity in one or more predictor variables into regression models for different types of outcome variables. Such nonlinear dependence is often not considered in applied research, yet non…

Edition
Ed. 1
ISBN/ISSN
978-3-319-33946-7
Collation
XXV, 372
Series Title
Statistics for Biology and Health
Call Number
519.5 KNA a
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Topological and Statistical Methods for Complex Data
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BANNETT, JanineVIVODTZEV, FabienPACUCCI, Valerio

This book contains papers presented at the Workshop on the Analysis of Large-scale, High-Dimensional, and Multi-Variate Data Using Topology and Statistics, held in Le Barp, France, June 2013. It features the work of some of the most prominent and recognized leaders in the field who examine challenges as well as detail solutions to the analysis of extreme scale data. The book presents new metho…

Edition
1
ISBN/ISSN
978-3-662-44900-4
Collation
XV, 297
Series Title
Mathematics and Visualization
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-
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cover
Introduction to Nonparametric Statistics for the Biological Sciences Using R
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Thomas W. MacFarlandJan M. Yates

This book contains a rich set of tools for nonparametric analyses, and the purpose of this text is to provide guidance to students and professional researchers on how R is used for nonparametric data analysis in the biological sciences: To introduce when nonparametric approaches to data analysis are appropriate To introduce the leading nonparametric tests commonly used in biostatistics and …

Edition
-
ISBN/ISSN
978-3-319-30634-6
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-
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-
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-
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First Page Previous 6 7 8 9 10 Last Page
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