heteroscedasticity
There are 0 repository under heteroscedasticity topic.
sailyshah / LinearRegression-CarPricePrediction
Car Price Prediction : Predictions made by using linear regression aaproach
Language:Jupyter Notebook 8- Language:R 3
pvh95 / ols_bootstrap
OLS Bootstrap on Cross-Sectional Data
Language:Jupyter Notebook 3vaitybharati / 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.
Language:Jupyter Notebook 3Supervised-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.
Language:Jupyter Notebook 3aaron1rcl / heteroscedastic_data
Various models and techniques to show how to handle heteroscedastic data
Language:Jupyter Notebook 1jcorrean / GAMLSS4PsycData
This repo provides supplemental material for the article titled: "Assessing Potential Heteroscedasticity in Psychological Data: A GAMLSS approach"
Language:HTML 1mamomen1996 / Python_CS_01
Traditional Regression problem project in Python
Language:HTML 1- Language:R 1
Supervised-ML---Multiple-Linear-Regression---Cars-dataset. Model MPG of a car based on other variables. 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.
Language:Jupyter Notebook 1WuCandice / Statistical-Analysis-on-US-Mortgage-Rates-Using-R
This project is about to use linear regression to examine the relationship between various economic variables and the mortgage rate in the United States.
Language:R 1Akashash01 / Akash_Linear-regression
This is an linear approach machine learning model used to predict the values of variable(dependent) based on other variables(independent).
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ChihLi / HetCalibrate
This R package allows calibration parameter estimation for inexact computer models with heteroscedastic errors proposed by Sung, Barber, and Walker (2022) in SIAM/ASA Journal on Uncertainty Quantification.
Language:R 0This instruction aims to reproduce the results in the paper “Calibration of inexact computer models with heteroscedastic errors” proposed by Sung, Barber, and Walker (2022).
Language:R 0ireneliu521 / BOPS-Strategy-Analysis_Project_R
Evaluate the Buy Online Pick-up in Store (BOPS) strategy with a real-world dataset
0olesyamba / ICvsML
Usual linear regression or XGBoost? Combo! Or how I was investigating the impact of intellectual capital on NASDAQ-100 capitalization during 2 years.
0PatilSukanya / Assignment-05.-Multiple-Linear-regression-Q2
Used libraries and functions as follows:
Language:Jupyter Notebook 0RezaDastranj / GAMM-ASDRs
Generalized Additive Forecasting Mortality
Language:CSS 0Age-Gender-Country-Specific Death Rates Modelling and Forecasting: A Linear Mixed-Effects Model
Language:CSS 0samuelzammit / EstCosmoPar-GPR-TPR
Estimation of the Hubble constant using Gaussian process regression and viable alternatives
Language:Python 0uweremer / regression_diagnostics
Skript zur Videoreihe Regressionsdiagnostik in R
Language:R 0venkatesh-eranti / Housing_case-study
A real estate company that has a dataset containing the prices of properties in the Delhi region. It wishes to use the data to optimise the sale prices of the properties based on important factors such as area, bedrooms, parking, etc
Language:Jupyter Notebook 0AndrMenezes / nlm2017
Course of Nonlinear Regression at UEM in 2017
Language:Rfiddlesleet / Linear-Regression
Recipes for common linear regression operations: model comparisons, heteroskedasticity, collinearity, goodness of fit
Language:RIsmail-therap / OLS-Regression-Analysis
Ordinary least square (OLS) regression analysis carried out in this project. The selected dependent variables are some public health indicators like anxiety, diabetes. We tried to find the independent variables which are responsible for this health hazard.
Language:Rtnathu-ai / time_series_analysis_in_R
time series analysis in R use cases
