How to describe or visualize a multiple linear regression model
I'm trying to fit a multiple linear regression model to my data with couple of input parameters, say 3.
regression - What does it mean to regress a variable against another ...
Dec 21, 2016 · Those words connote causality, but regression can work the other way round too (use Y to predict X). The independent/dependent variable language merely specifies how one thing depends …
regression - Why do we say the outcome variable "is regressed on" the ...
Apr 15, 2016 · In its core, linear regression amounts to orthogonal projection of y y on (onto) X X, where y y is the n n -dimensional vector of observations of the dependent variable and X X is the subspace …
What is the lasso in regression analysis? - Cross Validated
Oct 19, 2011 · LASSO regression is a type of regression analysis in which both variable selection and regulization occurs simultaneously. This method uses a penalty which affects they value of …
regression - When is R squared negative? - Cross Validated
Also, for OLS regression, R^2 is the squared correlation between the predicted and the observed values. Hence, it must be non-negative. For simple OLS regression with one predictor, this is equivalent to …
Hypotheses Testing - Correlation vs. Regression
Sep 4, 2023 · I conducted a survey for my thesis and would like to begin with the hypotheses testing now. However, I am not sure what the correct process is - sorry if these are really basic questions! …
Why not approach classification through regression?
86 "..approach classification problem through regression.." by "regression" I will assume you mean linear regression, and I will compare this approach to the "classification" approach of fitting a logistic …
Why Isotonic Regression for Model Calibration?
Jan 27, 2025 · 1 I think an additional reason why it is so common is the simplicity (and thus reproducibility) of the isotonic regression. If we give the same classification model and data to two …
How should outliers be dealt with in linear regression analysis ...
What statistical tests or rules of thumb can be used as a basis for excluding outliers in linear regression analysis? Are there any special considerations for multilinear regression?
Newest 'regression' Questions - Cross Validated
Q&A for people interested in statistics, machine learning, data analysis, data mining, and data visualization