Introduction to Python for Econometrics, Statistics and Numerical Analysis
by Kevin Sheppard
Number of pages: 281
Python is a widely used general purpose programming language, which happens to be well suited to Econometrics and other more general purpose data analysis tasks. These notes provide an introduction to Python for a beginning programmer. They may also be useful for an experienced Python programmer interested in using NumPy, SciPy, and matplotlib for numerical and statistical analaysis.
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by Thomas J. Rothenberg - Yale University Press
This book presents an attempt at unifying certain aspects of econometric theory by embedding them in a more general statistical framework. The unifying feature is the use of a priori information and the basic tool is the Cramer-Rao inequality.
by Wolfgang Härdle - Cambridge University Press
Nonparametric regression analysis has become central to economic theory. Hardle, by writing the first comprehensive and accessible book on the subject, contributed enormously to making nonparametric regression equally central to econometric practice.
by Charles Frederick Roos - Principia Press
Contents: Static Versus Dynamic Economics; Demand for Consumer Goods; Automotive Demand for Gasoline; Demand for Agricultural Products; Demand for Capital Goods; Factors Influencing Residential Building; Growth and Decline of Industry; etc.
by Harold T. Davis - The Principia Press
The object of this book is to set forth the present status of the problem of analyzing that very extensive set of data known as economic time series. This perplexing problem has engaged the attention of economists and statisticians for many years.