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Davidson J: Asymptotics for Fractional
Processes

Asymptotics for Fractional Processes

This book illustrates statistics with the R programming language, an emerging tool in data science. Filled with techniques for data science and analytics programming, the book is written for students and professionals. It is focused on learning outcomes and problem solving.

Demystifying Probability and Statistics for Data Scientists with R

World Scientific Lecture Notes In Economics And Policy

This book attempts to understand the operation and properties of 'market economies'. We do this by carefully examining, refining and in some cases extending the major theorems that Microeconomics has established in response to the Walrasian conjecture. We critically evaluate theorems and results, that assert the existence, uniqueness, stability, optimality and empirical relevance of Walrasian equilibrium states. As a result of our work, we attempt to comment on the wisdom of recommending that socio-economic systems operate as a collection of deregulated competitive markets.

Lectures In General Equilibrium Microeconomics

There is an increasing prevalence of large and complex datasets within the social sciences, and notably criminology in recent years. This data explosion has led to the development of specialized techniques for extracting information from such data. This book presents an introduction to "Big Data Science" for criminology and the social sciences, taking a case study-based approach to explaining the concepts. The theory is introduced as needed to answer scientific questions based on real data problems in the application areas. Some R and Python code is included to give support with implementation of the methods.

From Case Studies to Theory

Big Data Science for Criminology and the Social Sciences

This book introduces factor analysis methods for the study of multivariate stochastic processes whose structure evolves over time. It introduces the theory of factor analysis and evolutionary stochastic processes and combines that to study evolutionary factor models. The book includes many real examples to illustrate applications from such fields as macroeconomics, finance, neuroscience, communication, and psychology. MATLAB® and R code is included throughout the book for implementation of the methods.

Evolutionary Factor Analysis

This book illustrates how the choice of relevant data collection and data analysis techniques is critical for a sound and objective description of the complexity of space-time patterns and processes in ecology and the aquatic sciences. It reviews the concept of complexity in a general ecological context, before introducing a unifying definition of complexity in marine ecology. The book shows that convincing results can arise from very simple, sound, and well-thought-out approaches. The authors underline the risks related to modern techniques of data assimilation that can lead to data inundation, a loss of focus, and ultimately an erroneous scientific approach.

A Practical Guide to Avoid Becoming a Mistaken Scientist

Interpreting Ecological Complexity

Series On Multivariate Analysis

This is a thoroughly revised and updated edition of the earlier research monograph Topics in Circular Statistics by the first two authors. While maintaining the spirit as a research monograph, this book now covers the broader theme of directional statistics. Starting with an introduction to the area for those who wish to learn about this novel field, it goes on to survey the recent advances and developments in terms of theory, methodology, and applications. The book will be equally handy for the scientists in various application areas where methods based on directional data are being recognized as crucial and critical tools. As this novel area gets recognized as an important topic within statistics, this book can also serve as an essential resource for students to learn from.

Statistical Methods For Directional Data

Oxford Statistical Science Series

Statistical Modelling and Inference Using Likelihood

In All Likelihood

Chapman & Hall/CRC Interdisciplinary Statistics

An introduction to a new paradigm in social, technological, and scientific discourse, this book presents an overview of statistical methods for describing, modeling, and inferring biological networks using genomic and other types of data. It covers a large variety of modern statistical techniques, such as sparse graphical models, state space models, Boolean networks, and hidden Markov models. The authors address gene transcription data, microRNAs, ChIP-chip, and RNAi data. Along with end-of-chapter exercises, the text includes many real-world examples with implementations using a dedicated R package.

How to Infer Networks from Data

Statistics for Biological Networks

This text focuses on the parts of stochastic theory that are particularly relevant to applications. It begins with a description of Brownian motion and the associated stochastic calculus, including the relationship to partial differential equations. It then solves stochastic differential equations by a variety of methods. The author also studies in detail the one-dimensional case. The book concludes with a treatment of semigroups and generators, applying the theory of Harris chains to diffusions as well as weak convergence of Markov chains to diffusions.

An Elementary Introduction Emphasizing Applications

Stochastic Calculus

Professional Practice in Governance and Public Organizations

From Administrative Sources to Public Value

Data-Driven Learning in the EU

Routledge Textbooks in Development Economics

This book will guide the reader through both the basic and more advanced methods of impact evaluation, with a particular focus on impact evaluation within evidence-based policy making and in international development. The chapters provide a theoretical discussion of the various topics related to impact evaluation, complemented with exercises, case studies and worked examples drawn from the international development literature. Iconic impact evaluation studies will be used to exemplify the challenges of development impact evaluations.

The Essential Guide

Impact Evaluation for International Development

Statistical Analysis with Python For Dummies

Asymptotics for Fractional Processes

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