Publications by Arvind Sharma
Week 1:Bivariate Regression
Setting Up Working directory, clearing all data and memory # Clear the workspace rm(list = ls()) # Clear environment gc() # Clear unused memory ## used (Mb) gc trigger (Mb) limit (Mb) max used (Mb) ## Ncells 539941 28.9 1208047 64.6 NA 669282 35.8 ## Vcells 990762 7.6 8388608 64.0 32768 1840247 14.1 cat(...
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OLS:lm vs matrix algebra formula
1 Introduction One of the very first learning algorithms that you’ll encounter when studying data science and machine learning is least squares linear regression. Linear regression is one of the easiest learning algorithms to understand; it’s suitable for a wide array of problems, and is already implemented in many programming languages. Most...
4658 sym R (10085 sym/15 pcs)
Assignment1
1 Setup 1.1 Empty variables and functions in the environment tab/window First, empty the environment so that we can uplaod the clean data. # Clear the workspace rm(list = ls()) # Clear environment-remove all files from your workspace gc() # Clear unused memory ## used (Mb) gc trigger (Mb) limit (Mb) max used (Mb) ## Ncell...
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Fixed Effects
1 Intro Fixed effects regression can be done three ways: “n-1 binary regressors” method when n is small “Entity-demeaned” regression. “Changes” method when T = 2 FE estimator directly. 2 Setup # Clear the workspace rm(list = ls()) # Clear environment-remove all files from your workspace gc() # Clear unused memory ## ...
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Assignment 2 Solution Template
1 Setup 1.1 Empty variables and functions in the environment tab/window First, empty the environment so that we can uplaod the clean data. # Clear the workspace rm(list = ls()) # Clear environment-remove all files from your workspace gc() # Clear unused memory ## used (Mb) gc trigger (Mb) limit (Mb) max used (Mb) ## Ncell...
13382 sym R (58189 sym/63 pcs) 11 img