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Essential Statistics, Regression, and Econometrics
Essential Statistics, Regression, and Econometrics provides students with a readable, deep understanding of the key statistical topics they need to understand in an econometrics course. It is innovative in its focus, including real data, pitfalls in data analysis, and modeling issues (including functional forms, causality, and instrumental... | | Event History Analysis with R (Chapman & Hall/CRC The R Series)
With an emphasis on social science applications, Event History Analysis with R presents an introduction to survival and event history analysis using real-life examples. Keeping mathematical details to a minimum, the book covers key topics, including both discrete and continuous time data, parametric proportional... | | Level Sets and Extrema of Random Processes and FieldsLevel Sets and Extrema of Random Processes and Fields discusses how to understand the properties of the level sets of paths as well as how to compute the probability distribution of its extremal values, which are two general classes of problems that arise in the study of random processes and fields and in related applications. This book... |
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| | Practical Data Analysis
Transform, model, and visualize your data through hands-on projects, developed in open source tools
Overview
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Explore how to analyze your data in various innovative ways and turn them into insight
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Learn to use the D3.js visualization tool for exploratory data analysis
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| | Restricted Kalman Filtering: Theory, Methods, and Application (SpringerBriefs in Statistics)
In this book, I highlight the developments in Kalman filtering subject to general linear constraints. Essentially, the material to be presented is almost entirely based on the results and examples originally developed in Pizzinga et al. (2008a), Cerqueira et al. (2009), Pizzinga (2009, 2010), Souza et al. (2011), Pizzinga et al. (2011), and... |
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