Simultaneous equation methods (econometrics)
In econometrics, the seemingly unrelated regressions (SUR) or seemingly unrelated regression equations (SURE) model, proposed by Arnold Zellner in (1962), is a generalization of a linear regression model that consists of several regression equations, each having its own dependent variable and potentially different sets of exogenous explanatory variables. Each equation is a valid linear regression on its own and can be estimated separately, which is why the system is called seemingly unrelated, although some authors suggest that the term seemingly related would be more appropriate, since the error terms are assumed to be correlated across the equations. The model can be estimated equation-by-equation using standard ordinary least squares (OLS). Such estimates are consistent, however generally not as efficient as the SUR method, which amounts to feasible generalized least squares with a specific form of the variance-covariance matrix. Two important cases when SUR is in fact equivalent to OLS are when the error terms are in fact uncorrelated between the equations (so that they are truly unrelated) and when each equation contains exactly the same set of regressors on the right-hand-side. The SUR model can be viewed as either the simplification of the general linear model where certain coefficients in matrix are restricted to be equal to zero, or as the generalization of the general linear model where the regressors on the right-hand-side are allowed to be different in each equation. The SUR model can be further generalized into the simultaneous equations model, where the right-hand side regressors are allowed to be the endogenous variables as well. (Wikipedia).
An Introduction to Linear Regression Analysis
Tutorial introducing the idea of linear regression analysis and the least square method. Typically used in a statistics class. Playlist on Linear Regression http://www.youtube.com/course?list=ECF596A4043DBEAE9C Like us on: http://www.facebook.com/PartyMoreStudyLess Created by David Lon
From playlist Linear Regression.
Linear regression is used to compare sets or pairs of numerical data points. We use it to find a correlation between variables.
From playlist Learning medical statistics with python and Jupyter notebooks
Linear Regression t test and Confidence Interval Corrected
I introduce the Linear Regression t test and confidence intervals for the slope of a regression line. Find free review test, useful notes and more at http://www.mathplane.com If you'd like to make a donation to support my efforts look for the "Tip the Teacher" button on my channel's homepa
From playlist AP Statistics
Matt Moores - The Annealed Leap-Point MCMC Sampler (ALPS) for multi-modal posterior distributions
Dr Matt Moores (University of Wollongong) presents, "The Annealed Leap-Point MCMC Sampler (ALPS) for multi-modal posterior distributions", 10 June 2022.
From playlist Statistics Across Campuses
Principal Component Analysis (PCA) | Lê Nguyên Hoang
This video presents principal component analysis (PCA). Speaker and edition: Lê Nguyên Hoang. More on machine learning: https://www.youtube.com/playlist?list=PLie7a1OUTSagZB9mFZnVBgsNfBtcUGJWB
From playlist Data Science
An introduction to Regression Analysis
Regression Analysis, R squared, statistics class, GCSE Like us on: http://www.facebook.com/PartyMoreStudyLess Related Videos Playlist on Linear Regression http://www.youtube.com/playlist?list=PLF596A4043DBEAE9C Using SPSS for Multiple Linear Regression http://www.youtube.com/playlist?li
From playlist Linear Regression.
Uncoupled isotonic regression - Jonathan Niles-Weed
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From playlist Mathematics
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From playlist Coursera Regression V2
02 05 Part 2 of 3 Model Selection
From playlist Coursera Regression V2
Data Mining: The Tool of The Information Age
Learn how to explore, analyze, and leverage data sets of any scale in this 60-minute webinar with Google's Search Scientist and Stanford Instructor Rajan Patel. Learn more: http://scpd.stanford.edu/courses/data-mining-courses.jsp
From playlist Engineering
What is Multicollinearity? Extensive video + simulation!
See all my videos at http://www.zstatistics.com/videos/ 0:00 Introduction 2:16 Intuition 4:13 How does it affect our regression output? 6:55 Detection method I: Correlations 8:37 Detection method II: Variance Inflation Factors (VIFs) 11:50 Remedies 15:13 Justin's Simulation (COOL!) 22:17
From playlist Regression series (10 videos)
R - SEM - Path Analysis Class Assignment 2
Recorded: Summer 2015 Lecturer: Dr. Erin M. Buchanan Packages needed: lavaan, semPlot Class assignment for structural equation modeling. Topic covers how to put in correlation/covariance tables, create path models, run path models, create a picture of the model with semPaths, interpreting
From playlist Structural Equation Modeling
PAYMENTSfn 2019 - Lightning Talk: Are You Overlooking Data Gold? by Niaja Farve
PAYMENTSfn 2019 - Lightning Talk: Are You Overlooking Data Gold? by Niaja Farve #confreaks
From playlist PAYMENTSfn 2019
Trend Projection with Seasonality and Trends for Business Statistics
When we add the variable of time to our regression model, we can begin to make predictions father into the future. We look at linear trend regression which is the prediction when the trend is consistent over time, then explore seasonality and trends, allowing us to model both linear and cu
From playlist Business Statistics Lectures (FA2020, QBA337 @ MSU)
Why should you read “Moby Dick”? - Sascha Morrell
Dive into Herman Melville’s classic novel “Moby Dick,” the story of Captain Ahab’s hunt for revenge against the white whale who bit off his leg. -- A mountain separating two lakes. A room papered floor to ceiling with bridal satins. The lid of an immense snuffbox. These seemingly unrela
From playlist New TED-Ed Originals
Business Context: The Linchpin to Any Big Data Solution - Gregory Ursu (DIWO)
Subscribe to O'Reilly on YouTube: http://goo.gl/n3QSYi Follow O'Reilly on: Twitter: http://twitter.com/oreillymedia Facebook: http://facebook.com/OReilly Instagram: https://www.instagram.com/oreillymedia LinkedIn: https://www.linkedin.com/company-beta/8459/
From playlist Strata Solutions Showcase Theater 2017
R & Python - Linear Regression
Lecturer: Dr. Erin M. Buchanan Summer 2020 https://www.patreon.com/statisticsofdoom This video is part of my human language modeling class - this video set covers the updated version with both R and Python. Regression is a popular technique for continuous data - in this example, we talk
From playlist Human Language (ANLY 540)
Brief intro the the linear regression formula and errors.
From playlist Regression Analysis