In robust statistics, robust regression seeks to overcome some limitations of traditional regression analysis. A regression analysis models the relationship between one or more independent variables and a dependent variable. Standard types of regression, such as ordinary least squares, have favourable properties if their underlying assumptions are true, but can give misleading results otherwise (i.e. are not robust to assumption violations). Robust regression methods are designed to limit the effect that violations of assumptions by the underlying data-generating process have on regression estimates. For example, least squares estimates for regression models are highly sensitive to outliers: an outlier with twice the error magnitude of a typical observation contributes four (two squared) times as much to the squared error loss, and therefore has more leverage over the regression estimates. The Huber loss function is a robust alternative to standard square error loss that reduces outliers' contributions to the squared error loss, thereby limiting their impact on regression estimates. (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.
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.
From playlist Coursera Regression V2
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
Ex: Comparing Linear and Exponential Regression
This video provides an example on how to perform linear regression and exponential regression on the TI84. The best model is identified based up the value of R^2. Site: http://mathispower4u.com Blog: http://mathispower4u.wordpress.com
From playlist Solving Applications Using Exponential Equations / Compounded and Continuous Interest / Exponential Regression
We propose a sparse regression method capable of discovering the governing partial differential equation(s) of a given system by time series measurements in the spatial domain. The regression framework relies on sparsity promoting techniques to select the nonlinear and partial derivative
From playlist Research Abstracts from Brunton Lab
Peter BÜHLMANN - Robust, generalizable and causal-oriented machine learning
https://ams-ems-smf2022.inviteo.fr/
From playlist International Meeting 2022 AMS-EMS-SMF
Robust Principal Component Analysis (RPCA)
Robust statistics is essential for handling data with corruption or missing entries. This robust variant of principal component analysis (PCA) is now a workhorse algorithm in several fields, including fluid mechanics, the Netflix prize, and image processing. Book Website: http://databoo
From playlist Data-Driven Science and Engineering
Nexus Trimester - David Woodruff (IBM Almaden)
Sketching as a Tool for Numerical Linear Algebra and Recent Developments David Woodruff (IBM Almaden) March 03, 206 Abstract: We give near optimal algorithms for regression, low rank approximation, and robust variants of these problems. Our results are based on the sketch and solve parad
From playlist Nexus Trimester - 2016 - Central Workshop
HTE: Confounding-Robust Estimation
Professor Stefan Wager discusses general principles for the design of robust, machine learning-based algorithms for treatment heterogeneity in observational studies, as well as the application of these principles to design more robust causal forests (as implemented in GRF).
From playlist Machine Learning & Causal Inference: A Short Course
8ECM Plenary Lecture: Peter Bühlmann
From playlist 8ECM Plenary Lectures
Tradeoffs between Robustness and Accuracy - Percy Liang
More videos on http://video.ias.edu
From playlist Mathematics
Linear regression ANOVA ANCOVA Logistic Regression
In this video tutorial you will learn about the fundamentals of linear modeling: linear regression, analysis of variance, analysis of covariance, and logistic regression. I work through the results of these tests on the white board, so no code and no complicated equations. Linear regressi
From playlist Statistics
SINDy-PI: A robust algorithm for parallel implicit sparse identification of nonlinear dynamics
In this video, Kadierdan Kaheman describes SINDy-PI: A robust algorithm for parallel implicit sparse identification of nonlinear dynamics. The SINDy-PI overcomes the difficulties of using SINDy to identify the rational system or implicit dynamics and made it possible to directly extract th
From playlist Research Abstracts from Brunton Lab
David Haziza - Multiply robust imputation procedures for treatment of item nonresponse in surveys
Professor David Haziza (University of Ottawa) presents "Multiply robust imputation procedures for treatment of item nonresponse in surveys", 18 September 2020.
From playlist Statistics Across Campuses
Simplified Machine Learning Workflows with Anton Antonov, Session #5: Quantile Regression (Part 5)
Anton Antonov, a senior mathematical programmer, discusses the Quantile Regression Workflow in the Wolfram Language. You can find this content on the Wolfram Function Repository: https://resources.wolframcloud.com/FunctionRepository/resources/QuantileRegression You can directly interact
From playlist Simplified Machine Learning Workflows with Anton Antonov
We go over the entirety of seaborn's lmplot. We talk about factor grids and doing conditional linear regression. We talk about logistic, log transformed and lowess regression. This one was a big one, and a lot of fun, hope you enjoyed! Associated Github Commit: https://github.com/knathani
From playlist Seaborn: Understanding the Weird Parts
How to calculate Linear Regression using R. http://www.MyBookSucks.Com/R/Linear_Regression.R http://www.MyBookSucks.Com/R Playlist http://www.youtube.com/playlist?list=PLF596A4043DBEAE9C
From playlist Linear Regression.