Testing different models for the linear regression model with one estimator and heteroskedacity in data
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Updated
Jun 12, 2018 - TeX
Testing different models for the linear regression model with one estimator and heteroskedacity in data
Diagnostic tools for regression modeling. Julia-equivalent for diagnoser (https://github.com/robertschnitman/diagnoser).
Comprehensive tutorial notes for ETC2410 Introductory Econometrics
As part of this project, we have used Regression Analysis on top of a panel data on Guns in USA to determine the "Effect of Shall-Carry Law on Violence Rate and Incarceration Rate in United States".
Repo where different methods for price regression are used (supervised machine learning)
Econometrics_regression analysis using R language
The purpose of my application was to solve a problem many businesses (small businesses in particular) face. They do not know how much to produce, where to price, how much to spend on advertising and many other questions. Eden’s purpose was to answer these questions for them easily and with no technical acumen required by the user. Eden would mod…
Full Log-Likelihood Heteroskedastic Regression with Deep Neural Networks and Tensorflow
An R package for time series modelling with mixture autoregressive and related models.
Script used for my undergraduate thesis
Diagnostic tools for regression modeling.
R Code for Bayesian Inference for Structural Vector Autoregressions Identified with Markov-Switching Heteroskedasticity
Sketching of Data via Random Subspace Embeddings
GWAS of trait variance (C++)
R package to perform regression-based Brown-Forsythe test
Here I have checked and removed for heteroskedasticity .
Impact of macroecomonic variables on S&P 500
OLS regression with possibility of controlling for fixed effects and robust standard errors
Linear Multilinear and Logistic Regression in Machine Learning
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