Econometrics and economic statistics

The beginning of the age of artificial intelligence and machine learning has created new challenges and opportunities for data analysts, statisticians, mathematicians, econometricians, computer scientists and many others.

Praise for the first edition:[This book] reflects the extensive experience and significant contributions of the author to non-linear and non-Gaussian modeling.

Praise for the first edition:[This book] reflects the extensive experience and significant contributions of the author to non-linear and non-Gaussian modeling.

Originally published in 1971, this is a rigorous analysis of the economic aspects of the efficiency of public enterprises at the time.

From a review of the first edition: "e;Modern Data Science with R.

Originally published in 1971, this is a rigorous analysis of the economic aspects of the efficiency of public enterprises at the time.

From a review of the first edition: "e;Modern Data Science with R.

Introduction to Financial Mathematics: Option Valuation, Second Edition is a well-rounded primer to the mathematics and models used in the valuation of financial derivatives.

This book introduces computational advertising, and Internet monetization.

Introduction to Financial Mathematics: Option Valuation, Second Edition is a well-rounded primer to the mathematics and models used in the valuation of financial derivatives.

This book introduces computational advertising, and Internet monetization.

Modelling Spatial and Spatial-Temporal Data: A Bayesian Approach is aimed at statisticians and quantitative social, economic and public health students and researchers who work with spatial and spatial-temporal data.

Time Series: A First Course with Bootstrap Starter provides an introductory course on time series analysis that satisfies the triptych of (i) mathematical completeness, (ii) computational illustration and implementation, and (iii) conciseness and accessibility to upper-level undergraduate and M.

The book's website (with databases and other support materials) can be accessed here.

The book's website (with databases and other support materials) can be accessed here.

Bayesian Statistical Methods provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis.

Bayesian Statistical Methods provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis.

Practical Spreadsheet Modeling Using @Risk provides a guide of how to construct applied decision analysis models in spreadsheets.

Practical Spreadsheet Modeling Using @Risk provides a guide of how to construct applied decision analysis models in spreadsheets.

Spatial statistics are useful in subjects as diverse as climatology, ecology, economics, environmental and earth sciences, epidemiology, image analysis and more.

This book provides a synthesis of some recent issues and an up-to-date treatment of some of the major important issues in distributional analysis that I have covered in my previous book Ethical Social Index Numbers, which was widely accepted by students, teachers, researchers and practitioners in the area.

"e;Mathematical Optimization and Economic Analysis"e; is a self-contained introduction to various optimization techniques used in economic modeling and analysis such as geometric, linear, and convex programming and data envelopment analysis.

This book gives you a step-by-step introduction to analysing time series using the open source software R.

Managers are often under great pressure to improve the performance of their organizations.

R is a language and environment for data analysis and graphics.

Quantitative finance is a combination of economics, accounting, statistics, econometrics, mathematics, stochastic process, and computer science and technology.

Financial globalization has increased the significance of methods used in the evaluation of country risk, one of the major research topics in economics and finance.

The analysis of integrated and co-integrated time series can be considered as the main methodology employed in applied econometrics.

Stochastic di?

We began writing this book in parallel with developing software for handling and analysing spatial data withR (R Development Core Team, 2008).

One of the most pressing problems in today's health care system is performance evaluation.

Feasibility and Infeasibility in Optimization is an expository book focused on practical algorithms related to feasibility and infeasibility in optimization.

Exceptional managers know that they can create competitive advantages by basing decisions on performance response under alternative scenarios.

Multilevel analysis is the statistical analysis of hierarchically and non-hierarchically nested data.

A wide variety of processes occur on multiple scales, either naturally or as a consequence of measurement.

Recurrent event data arise in diverse fields such as medicine, public health, insurance, social science, economics, manufacturing and reliability.

Amongmanyexcitingdevelopmentsinstatisticsoverthelasttwodecades, nonlineartimeseriesanddata-analyticnonparametricmethodshavegreatly advanced along seemingly unrelated paths.

Jean-Jacques Rousseau wrote in the Preface to his famous Discourse on Inequality that "e;I consider the subject of the following discourse as one of the most interesting questions philosophy can propose, and unhappily for us, one of the most thorny that philosophers can have to solve.

DEA is computational at its core and this book will be one of several books that we will look to publish on the computational aspects of DEA.

This is the second volume of a text on the theory and practice of maximum penalized likelihood estimation.

WhenIwrotethebookMethodsofMomentsandSemiparametricEco- metrics for Limited Dependent Variable Models published from Springer in 1996, my motivation was clear: there was no book available to convey the latest messages in micro-econometrics.

Proportional hazards models and their extensions (models with ti- dependent covariates, models with time dependent regression co- cients, models with random coe?

The aim of this book is to bridge the gap between standard textbook models and a range of models where the dynamic structure of the data manifests itself fully.

Frederick Mosteller has inspired numerous statisticians and other scientists by his creative approach to statistics and its applications.

Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References, And DEA-Solver Software, 2nd Edition is designed to provide a systematic introduction to DEA and its uses as a multifaceted tool for evaluating problems in a variety of contexts.

Modern apparatuses allow us to collect samples of functional data, mainly curves but also images.