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 …
Why don't we see Copula Models as much as Regression Models?
Jan 23, 2022 · My first guess as to why Copula Models are less widespread compared to Regression Models, is that the framework and mathematics required in Copulas is arguably far …
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 - 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 …
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 - 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 …
Support Vector Regression vs. Linear Regression - Cross Validated
Dec 5, 2023 · Linear regression can use the same kernels used in SVR, and SVR can also use the linear kernel. Given only the coefficients from such models, it would be impossible to …
CNN architectures for regression? - Cross Validated
Mar 21, 2018 · Group equivariant CNNs are more mature than steerable CNNs from an implementation point of view, so I’d try group CNNs first. You can try the classification-then …
Modelling mortality rates using Poisson regression
Dec 14, 2014 · The Poisson regression doesn't care whether the data as aggregated or not, but in practice non-aggregated data is frail and can cause some unexpected errors. Note that you …
correlation - What is the difference between linear regression on y ...
The Pearson correlation coefficient of x and y is the same, whether you compute pearson(x, y) or pearson(y, x). This suggests that doing a linear regression of y given x or x given y should be …