Publications by Arvind Sharma
R Markdown Basics
Can replace ‘html_document’ with ‘pdf_document’ in the .Rmd (Rmarkdown) file above manually to generate the output in your preferred format. However, I would strongly suggest using HTML format initially as the setup is likely to reduce math symbol issues if you do not have Latex installed locally. Also, make sure to change the settings of t...
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OLS: From Scratch using Matrix Algebra in R
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 u...
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Preview: Running a regression and residual analysis in R
1 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 526249 28.2 1168927 62.5 NA 669282 35.8 ## Vcells 967551 7.4 8388608 64.0 32768 1840394 14.1 cat(...
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Bankruptcy_Paper_Miniator_CrossCheck
Correlation Function # Clear the environment by removing all objects from memory remove(list = ls()) # Define a function for computing correlations and creating a correlation plot corfunction <- function(d) { # Compute the correlation matrix mycorr <- cor(d[, 1:ncol(d)]) # Compute the p-values for correlations p.mat <- ggcorrplot::cor_pma...
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WLS
1 INTRO Weighted least squares (WLS) is a method of fitting a linear regression model where the errors are not homoscedastic (i.e., they have unequal variances). In WLS, the model is fitted by minimizing the weighted sum of squared residuals, where each residual is multiplied by a weight that is proportional to the inverse of the variance of the co...
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HW2_solution
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) ## Ncells ...
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IV_JEC_example
1 Import Data Raw Data from https://github.com/R-Avalos/JEC remove(list=ls()) library(readxl) ?read_excel JEC_data <- read_excel("~/Library/CloudStorage/Dropbox/WCAS/Econometrics/share/shared/W6/JEC_data.xlsx") library("psych") describe(JEC_data) ## vars n mean sd median trimmed mad min max ## week* 1 32...
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Count_Regressions_Implementation
1 Data We use the data set "warpbreaks". This data set gives the number of warp breaks per loom, where a loom corresponds to a fixed length of yarn. remove(list=ls()) ?warpbreaks df <- warpbreaks print(head(df)) ## breaks wool tension ## 1 26 A L ## 2 30 A L ## 3 54 A L ## 4 25 A L ## 5 70 ...
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QTM
1 Quantity Theory Equation We want to test whether quantity theory of money holds or not. M * V = P * T where M is money supply: https://fred.stlouisfed.org/series/WM2NS V is velocity of money: https://fred.stlouisfed.org/series/M2V P is price level: https://fred.stlouisfed.org/series/CPIAUCSL#0 T is transactions: https://fred.stlouisfed.org/serie...
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Lasso_Ridge
1 SetUp # 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) ## Ncells 524036 28.0 1162601 62.1 NA 669288 35.8 ## Vcells 964993 7.4 8388608 64.0 32768 1840228 14.1 cat("\f") ...
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