niekdt/meanvar-clustering-longitudinal-data

Supplementary materials for the manuscript "Latent-class trajectory modeling with a heterogeneous mean-variance relation" by N. G. P. Den Teuling, F. Ungolo, S.C. Pauws, and E.R. van den Heuvel

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GeoBosh/mixAR

An R package for time series modelling with mixture autoregressive and related models.

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sokbae/sketching

Sketching of Data via Random Subspace Embeddings

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robertschnitman/diagnoser

Diagnostic tools for regression modeling.

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robertschnitman/diagnoserjl

Diagnostic tools for regression modeling. Julia-equivalent for diagnoser (https://github.com/robertschnitman/diagnoser).

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Avinash793/regression-analysis-examples

Detailed implementation of various regression analysis models and concepts on real dataset.

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gepapago/Empirical-Research

Basic methodologies of Empirical Research applied on various case studies (R language)

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Sarthak-Mohapatra/Effect-of-Shall-Carry-Law-on-Violence-Rate-in-United-States

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".

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katlass/Umass-Senior-Project-2019

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 model supply and demand equations using ordinary least squares (OLS) regression on the user’s data to form the best fitting supply and demand equations possible. The best fit was to be ensured by regressing each variable against demand or supply, determine the best shape via the highest adjusted R2, and then do an OLS regression and simplistically tell the user what the results mean. Eden would attempt multiple shapes like linear, logarithmic, cubic, quadratic, and inverse. The user interface would be easy to navigate and user-friendly.

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VFCI/vfci

Code to reproduce paper Adrian, Duarte and Iyer (2023), “The Market Price of Risk and Macro-Financial Dynamics”

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quangvanbui/introductory-econometrics

Comprehensive tutorial notes for ETC2410 Introductory Econometrics

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ferdynandariza/fgls

Script used for my undergraduate thesis

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rishabhgupta91/Macroeconomic-Variables-and-SandP-500-Performance

Impact of macroecomonic variables on S&P 500

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MRCIEU/varGWAS

GWAS of trait variance (C++)

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MRCIEU/varGWASR

R package to perform regression-based Brown-Forsythe test

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calosor/ols_regression

OLS regression with possibility of controlling for fixed effects and robust standard errors

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akash2262/P6-heteroskedasticity-checking

Here I have checked and removed for heteroskedasticity .

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Zoey1102/heteroskedasticity

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claCase/Heteroskedasticity-DNN

Full Log-Likelihood Heteroskedastic Regression with Deep Neural Networks and Tensorflow

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evajryang/Econometrics-RegressionAnalysis

Econometrics_regression analysis using R language

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