Showing results for "Nonlinear Statistical Models English"

Human movement variability can be defined as the typical variations that are present in motor performance and are observed across multiple repetitions of a task. This variability is inherent within all biological systems. It can also be observed easily as it is almost impossible for an individual, even an elite performer, to perform two identical actions of the same task. Nonlinear Analysis for Human Movement Variability, Second edition presents a different approach to studying hu...

Taking advantage of both user-developed code and specialized functions, this second edition of An R Companion to Linear Statistical Models again targets two primary audiences: Those who are familiar with the introductory theory and applications of linear statistical models and who wish to learn how to use R in this area, or explore further ideas that might appear in this Companion; and those who are enrolled in an intermediate to advanced level course on linear st...

Make data-driven, informed decisions and enhance your statistical expertise in Python by turning raw data into meaningful insights Purchase of the print or Kindle book includes a free PDF eBookKey FeaturesGain expertise in identifying and modeling patterns that generate successExplore the concepts with Python using important libraries such as stats modelsLearn how to build models on real-world data sets and find solutions to practical challenge...

Statistical Models in S extends the S language to fit and analyze a variety of statistical models, including analysis of variance, generalized linear models, additive models, local regression, and tree-based models. The contributions of the ten authors-most of whom work in the statistics research department at AT&T Bell Laboratories-represent results of research in both the computational and statistical aspects of modeling data.

Dive into the fascinating realm of data with "Statistical Analysis for Beginners: A Hands-On Approach to Unraveling Data Mysteries and Transforming Numbers into Knowledge." This comprehensive guide is crafted for those seeking to demystify the world of statistics and harness the power of data in their hands. Unlock the Secrets of Numbers: Embark on a journey that transforms raw data into valuable insights. This book introduces beginners to the fundamental concept...

Nonlinear Integro-Differential Equations demonstrates how integro-differential equations provide a powerful mathematical framework for modeling complex systems that exhibit history-dependent behavior, feedback mechanisms, and nonlocal effects. Complex phenomena demand sophisticated analytical tools capable of capturing memory, hereditary properties, and spatial interactions simultaneously. This resource shows how nonlinear integro-differential equations address these modeling challenges ef...

Real-world issues can be translated into the language and concepts of mathematics with the use of mathematical models. Models guided by differential equations with intuitive solutions can be used throughout engineering and the sciences. Almost any changing system may be described by a set of differential equations. They may be found just about anywhere you look in fields including physics, engineering, economics, sociology, biology, business, healthcare, etc. The nature of these equations ...

This book on statistical models and learning methods for complex data comprises a selection of peer-reviewed post-conference papers presented at the 14th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society (CLADAG 2023), held in Salerno, Italy, September 11–13, 2023. The contributions span a variety of topics, including different approaches to clustering and classification, multidimensional data analysis, panel data, social networks, time ser...

This book investigates several competing forecasting models for interest rates, financial returns, and realized volatility, addresses the usefulness of nonlinear models for hedging purposes, and proposes new computational techniques to estimate financial processes.

Nonlinear models have been used extensively in the areas of economics and finance. Recent literature on the topic has shown that a large number of series exhibit nonlinear dynamics as opposed to the alternative--linear dynamics. Incorporating these concepts involves deriving and estimating nonlinear time series models, and these have typically taken the form of Threshold Autoregression (TAR) models, Exponential Smooth Transition (ESTAR) models, and Markov Switching (MS) models, among sever...

This book presents a collection of significant and original contributions that delve into the realm of nonlinear evolution equations and their applications, encompassing both theory and practical usage. Serving as a dynamic platform for interdisciplinary collaboration, it facilitates the exchange of innovative ideas among scientists from diverse fields who share a keen interest in the intricate world of evolution equations. The book bridges the gap between theory and practicality, offering...

This book aims to explore the scale invariance present in certain nonlinear dynamical systems. We will discuss both ordinary differential equations (ODEs) and discrete-time maps. The loss of predictability in the temporal evolution of nearby initial conditions, and the resulting exponential divergence of their trajectories in phase space, leads to the concept of chaos. Some observables studied in nonlinear systems exhibit characteristics that can be described through scaling laws, giving r...