“I’d like to introduce you to a new book I just published that might be of interest to you: Using R for Introductory Econometrics. The goal: An introduction to R that makes it as easy as possible for undergrad students to link theory to practice without any hurdles regarding material, ...
In particular, the library, multiprocessing in Python (v3.6.6), packages foreach - doParallel in R (v4.0.0) and GNU Parallel in Ubuntu Linux v18.04.5 (Tange, 2011) were used for parallel processing. Geospatial Data Abstraction Library (GDAL) (GDAL/OGR contributors, 2020) was used for ...
All analysis was performed within the UCL Data Safe Haven using Python (version 3.8), spyder (version 4.1.4), pandas (version 1.0.5) [67], [68], and statsmodels (version 0.11.1) [69] for the linear mixed effects regressions. The code used to perform the analysis of SERL data presente...
Business Statistics Using R by Mustapha Akinkunmi. Business Statistics Using R covers a wide range of applications of statistics in solving business related problems. It will introduce readers to
Causal InferenceWhat If: Python Code for Causal Inference: What If mostly-harmless-replication: Mostly Harmless Econometrics: An Empiricist's Companion 社会经济政策的计量经济学评估:理论与应用: 社会经济政策的计量经济学评估:理论与应用 合成控制法专栏精选资源 ...
Statistics for Machine Learning: Techniques for Exploring Supervised, Unsupervised, and Reinforcement Learning Models with Python and R; Packt Publishing: Birmingham, UK, 2017. 43. Brooks, C. Introductory Econometrics for Finance, 2nd ed.; Cambridge University Press: Cambridge, UK, 2008. 44. Hastie...
Statistics for Machine Learning: Techniques for Exploring Supervised, Unsupervised, and Reinforcement Learning Models with Python and R; Packt Publishing: Birmingham, UK, 2017. [Google Scholar] Brooks, C. Introductory Econometrics for Finance, 2nd ed.; Cambridge University Press: Cambridge, UK, 2008....