Econometrics and Data Science: Apply Data Science Techniques to Model Complex Problems and Implement Solutions for Economic Problems, Nokeri Tshepo Chris
Автор: Cameron Название: Regression Analysis of Count Data ISBN: 1107667275 ISBN-13(EAN): 9781107667273 Издательство: Cambridge Academ Рейтинг: Цена: 8078.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Students in both social and natural sciences often seek regression methods to explain the frequency of events, such as visits to a doctor, auto accidents, or new patents awarded. The second edition provides the most comprehensive and up-to-date account of models and methods to interpret such data.
Автор: Cameron Название: Regression Analysis of Count Data ISBN: 1107014166 ISBN-13(EAN): 9781107014169 Издательство: Cambridge Academ Рейтинг: Цена: 22176.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Students in both social and natural sciences often seek regression methods to explain the frequency of events, such as visits to a doctor, auto accidents, or new patents awarded. The second edition provides the most comprehensive and up-to-date account of models and methods to interpret such data.
Автор: Hsiao, Cheng, Название: Analysis of Panel Data ISBN: 1107657636 ISBN-13(EAN): 9781107657632 Издательство: Cambridge Academ Рейтинг: Цена: 5859.00 р. Наличие на складе: Поставка под заказ.
Описание: This book provides a comprehensive, coherent, and intuitive review of panel data methodologies that are useful for empirical analysis. Substantially revised from the second edition, it includes two new chapters on modeling cross-sectionally dependent data and dynamic systems of equations. Some of the more complicated concepts have been further streamlined. Other new material includes correlated random coefficient models, pseudo-panels, duration and count data models, quantile analysis, and alternative approaches for controlling the impact of unobserved heterogeneity in nonlinear panel data models.
Описание: With the help of practical examples and engaging activities, The Reinforcement Learning Workshop takes you through reinforcement learning`s core techniques and frameworks. Following a hands-on approach, it allows you to learn reinforcement learning at your own pace to develop your own intelligent applications with ease.
Описание: Non-extensive Entropy Econometrics for Low Frequency Series provides a new and robust power-law-based, non-extensive entropy econometrics approach to the economic modelling of ill-behaved inverse problems.
Описание: Figure 1. 4: First order neighbours (a) and second order neighbours (b) of a reference area. a shows the first-order neighbours of a reference area, while Figure 1. While it is clear that the dependence is strongest between immediate neighbouring areas a certain degree of dependence may be present among higher-order neighbours.
Автор: Pierre Duchesne; Bruno R?millard Название: Statistical Modeling and Analysis for Complex Data Problems ISBN: 144193751X ISBN-13(EAN): 9781441937513 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Statistical Modeling and Analysis for Complex Data Problems treats some of today's more complex problems and it reflects some of the important research directions in the field. Twenty-nine authors - largely from Montreal's GERAD Multi-University Research Center and who work in areas of theoretical statistics, applied statistics, probability theory, and stochastic processes - present survey chapters on various theoretical and applied problems of importance and interest to researchers and students across a number of academic domains.
Описание: This volume presents techniques and theories drawn from mathematics, statistics, computer science, and information science to analyze problems in business, economics, finance, insurance, and related fields. The authors present proposals for solutions to common problems in related fields. To this end, they are showing the use of mathematical, statistical, and actuarial modeling, and concepts from data science to construct and apply appropriate models with real-life data, and employ the design and implementation of computer algorithms to evaluate decision-making processes. This book is unique as it associates data science - data-scientists coming from different backgrounds - with some basic and advanced concepts and tools used in econometrics, operational research, and actuarial sciences. It, therefore, is a must-read for scholars, students, and practitioners interested in a better understanding of the techniques and theories of these fields.
Автор: Hilbe Название: Modeling Count Data ISBN: 1107028337 ISBN-13(EAN): 9781107028333 Издательство: Cambridge Academ Рейтинг: Цена: 15365.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Written for researchers with little or no background in advanced statistics, this book provides guidelines and fully worked examples of how to select, construct, interpret and evaluate the full range of count models. Stata, R, and SAS code enable readers in a variety of disciplines to adapt models for their own purposes.
Автор: Kim P. Huynh, David T. Jacho-Chavez, Gautam Tripathi Название: The Econometrics of Complex Survey Data: Theory and Applications ISBN: 1787567265 ISBN-13(EAN): 9781787567269 Издательство: Emerald Рейтинг: Цена: 17683.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume of Advances in Econometrics contains a selection of papers presented at the `Econometrics of Complex Survey Data: Theory and Applications` conference organized by the Bank of Canada, Ottawa, Canada, from October 19-20, 2017.
Описание: This book is an extension of the author`s first book and serves as a guide and manual on how to specify and compute 2-, 3-, and 4-Event Bayesian Belief Networks (BBN).
Автор: Hilbe Название: Modeling Count Data ISBN: 1107611253 ISBN-13(EAN): 9781107611252 Издательство: Cambridge Academ Рейтинг: Цена: 6018.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Written for researchers with little or no background in advanced statistics, this book provides guidelines and fully worked examples of how to select, construct, interpret and evaluate the full range of count models. Stata, R, and SAS code enable readers in a variety of disciplines to adapt models for their own purposes.
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