regression - What does it mean to regress a variable against …
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 …
Why Isotonic Regression for Model Calibration?
Jan 27, 2025 · It appears that isotonic regression is a popular method to calibrate models. I understand that isotonic guarantees a monotonically increasing or decreasing fit. However, if …
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 …
Regression based on rank observations - Cross Validated
Apr 6, 2025 · The coefficients of an OLS regression are just simple descriptive statistics; you can compute them on any data, w/o having to make any assumption whatsoever, just as you could …
regression - Trying to understand the fitted vs residual plot?
Dec 23, 2016 · A good residual vs fitted plot has three characteristics: The residuals "bounce randomly" around the 0 line. This suggests that the assumption that the relationship is linear is …
normalization - Normalized regression coefficients - interpretation ...
Apr 24, 2020 · I have data containing several variables. I ran a regression model. Prior to running the model I have normalized the dependent variable Y and the independent variables X1 and …
regression - How to calculate the slope of a line of best fit that ...
Dec 17, 2024 · This kind of regression seems to be much more difficult. I've read several sources, but the calculus for general quantile regression is going over my head. My question is this: …
predictive models - Cox regression vs logistic/simple regression ...
Jan 1, 2020 · Logistic regression is used when modelling the probability of an event happening, which will usually mean that the response variable is binary. The model provides odds ratios …
Log-linear regression vs. Poisson regression - Cross Validated
I find "log-linear regression" to be somewhat of a misnomer since the whole idea extends to much more than just plain regression (probably why wikipedia calls it log-linear analysis. Log-linear …
regression - Linear model with both additive and multiplicative …
Sep 23, 2020 · In a log-level regression, the independent variables have an additive effect on the log-transformed response and a multiplicative effect on the original untransformed response: