ols-regression
There are 186 repositories under ols-regression topic.
JuliaStats/MultivariateStats.jl
A Julia package for multivariate statistics and data analysis (e.g. dimension reduction)
marcelomijas/econometrics-cheatsheet
Multiple econometrics cheat sheets with a complete and summarize review going from the basics of an econometric model to the solution of the most popular problems.
olmallet81/URT
Fast Unit Root Tests and OLS regression in C++ with wrappers for R and Python
TatevKaren/econometric-algorithms
Popular Econometrics content with code; Simple Linear Regression, Multiple Linear Regression, OLS, Event Study including Time Series Analysis, Fixed Effects and Random Effects Regressions for Panel Data, Heckman_2_Step for selection bias, Hausman Wu test for Endogeneity in Python, R, and STATA.
faosorios/fastmatrix
Fast computation of some matrices useful in statistics
aeturrell/specification_curve
Specification Curve is a Python package that performs specification curve analysis: exploring how a coefficient varies under multiple different specifications of a statistical model.
BendeguzBiksi/Master-Studies-Econometrics-I
Master Degree Coursework: Econometrics I
vaitybharati/Assignment-04-Simple-Linear-Regression-2
Assignment-04-Simple-Linear-Regression-2. Q2) Salary_hike -> Build a prediction model for Salary_hike Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization. Correlation Analysis. Model Building. Model Testing. Model Predictions.
julzerinos/r-structural-breaks-with-ml
Detecting structural breaks in time series data using statistical analysis and regression models in R.
Guoliang2019/Oil-Price-Modeling-with-Machine-Learning-Methods
Construct workable datasets from web data and applied various machine learning methods to predict future oil price
sahilichake/Indian-Crime-Data-Analysis-Forecasting
Conducted data analysis, statistical analysis, and data visualization on an Indian crime dataset. Applied various machine learning algorithms to gain insights from the data. Utilized Time-Series models for prediction and forecasting based on the crime data analysis.
AbdirayimovS/Multiple_Regression_project
Apex team`s multiple regression project. It contains: What is Multiple Regression? Advantages and disadvantages of multiple regression, least square method and real implementation.
boyla950/predicting-the-pound
MSc Finance dissertation project at Newcastle University. This project focused on forecasting the volatility of exchange rates involving the Great British Pound using EWMA, GARCH-type and Implied Volatility models.
imnikhilanand/Bayesian-Marketing-Mix-Modeling
The project analyses the impact of different marketing tactics on the sales of items. The problem is a multivariate-modeling problem as there are 3 different tactics of marketing. Since, the impact of marketing medium cannot be negative we will be using Bayesian model for regression.
mateoservent/coefeasy
Coefeasy is an R package under development for making regression coefficients more accessible. With this tool, you can read and report key coefficients instantly.
vaitybharati/Assignment-05-Multiple-Linear-Regression-2
Assignment-05-Multiple-Linear-Regression-2. Prepare a prediction model for profit of 50_startups data. Do transformations for getting better predictions of profit and make a table containing R^2 value for each prepared model. R&D Spend -- Research and devolop spend in the past few years Administration -- spend on administration in the past few years Marketing Spend -- spend on Marketing in the past few years State -- states from which data is collected Profit -- profit of each state in the past few years.
BendeguzBiksi/Master-Studies-Econometrics-II
Master Degree Coursework: Econometrics II
govardhan26/Linear-regression
Linear regression on numerical attributes
rakeshjasti/Car-MPG
Predicting miles per gallon (MPG) for a car using UCI dataset
sanketmaneDS/Simple_Linear_Regression
This repository introduces reader to basic concepts of simple linear regression and its application.
vaitybharati/Assignment-04-Simple-Linear-Regression-1
Assignment-04-Simple-Linear-Regression-1. Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization, Feature Engineering, Correlation Analysis, Model Building, Model Testing and Model Predictions using simple linear regression.
vaitybharati/P24.-Supervised-ML---Simple-Linear-Regression---Newspaper-data
Supervised-ML---Simple-Linear-Regression---Newspaper-data. EDA and Visualization, Correlation Analysis, Model Building, Model Testing, Model predictions.
vaitybharati/P27.-Supervised-ML---Multiple-Linear-Regression---Toyoto-Cars
Supervised-ML---Multiple-Linear-Regression---Toyota-Cars. EDA, Correlation Analysis, Model Building, Model Testing, Model Validation Techniques, Collinearity Problem Check, Residual Analysis, Model Deletion Diagnostics (checking Outliers or Influencers) Two Techniques : 1. Cook's Distance & 2. Leverage value, Improving the Model, Model - Re-build, Re-check and Re-improve - 2, Model - Re-build, Re-check and Re-improve - 3, Final Model, Model Predictions.
bvtvusn/Magnet-based-encoder
Encoder using magnetometer on Arduino nano 33 BLE
jeevankande/Time-Series-and-Survival-Analytics
Time series forecasting occurs when you make scientific predictions based on historical time stamped data. It involves building models through historical analysis and using them to make observations and drive future strategic decision-making. An important distinction in forecasting is that at the time of the work, the future outcome is completely unavailable and can only be estimated through careful analysis and evidence-based priors.
KevinDepedri/AI-for-Finance
Stock market prediction on 5 italian companies using VAR model, OLS regressions and LSTM recurrent neural networks over data retrieved from Refinitiv Eikon
myupeshkov/Econometrics_HSE
Econometrics courses (Coursera and HSE)
north0n-FI/Multivariate-Regression---King-County-House-Prices
Supervised Machine Learning Using Regression Analysis
nvlinhvn/water-consumption-campaign-analytics
Evaluate the effectiveness of water consumption campaign in 12 districts
omledufromage/Intro-to-Econometrics-Python-assignment
Python programming assignment developing a simulation study and exploring the OLS estimator.
SMQuadri/Geely-Car-Price-Prediction
Machine Learning Project
sumeetkotaria11/BitcoinAnalysis
This project is aimed at analyzing and predicting Bitcoin price fluctuation using Natural Language Processing on Twitter data and subsequently applying VADER sentiment analysis.
svmiller/eh6105
Quantitative Methods (EH6105)
vaitybharati/P25.-Supervised-ML---Simple-Linear-Regression---Waist-Circumference-Adipose-Tissue-Data
Supervised-ML---Simple-Linear-Regression---Waist-Circumference-Adipose-Tissue-Data. EDA and data visualization, Correlation Analysis, Model Building, Model Testing, Model Prediction.
AScick/Machine_Learning_Project
Bunch of exercises computed during the Machine Learning for Finance course.
ShaikRiyazSandy/Simple-Linear-Regression
Simple Linear Regression