“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
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...
Ideal Skills: - Proficiency in Python or R for implementing machine learning algorithms. - Experience with cancer datasets is a plus. - Strong understanding of model evaluation metrics. Please use the original version of the Wisconsin Breast Cancer dataset. Please use Python with scikit-learn for ...
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...