Top "Regression" questions

Regression analysis is a collection of statistical techniques for modeling and predicting one or multiple variables based on other data.

How to extract a p-value when performing anova() between two glm models in R

So, I'm trying to compare two models, fit1 and fit2. Initially, I was just doing anova(fit1,fit2), and this …

r model regression glm anova
Non-linear regression in C#

I'm looking for a way to produce a non-linear (preferably quadratic) curve, based on a 2D data set, for predictive …

c# math machine-learning statistics regression
Getting statsmodels to use heteroskedasticity corrected standard errors in coefficient t-tests

I've been digging into the API of statsmodels.regression.linear_model.RegressionResults and have found how to retrieve different flavors …

python regression statsmodels
Python threading error - must be an iterable, not int

I'm trying to calculate rolling r-squared of regression among first column and other columns in a dataframe (first column and …

python multithreading regression python-multithreading iterable
Logistic regression with robust clustered standard errors in R

A newbie question: does anyone know how to run a logistic regression with clustered standard errors in R? In Stata …

r regression stata
What function defines accuracy in Keras when the loss is mean squared error (MSE)?

How is Accuracy defined when the loss function is mean square error? Is it mean absolute percentage error? The model …

machine-learning keras regression loss-function mean-square-error
How to implement the Softmax derivative independently from any loss function?

For a neural networks library I implemented some activation functions and loss functions and their derivatives. They can be combined …

neural-network regression backpropagation derivative softmax
Lasso r code - what is wrong with it?

I am attempting to carry out lasso regression using the lars package but can not seem to get the lars …

r regression lasso-regression lars
python stats models - quadratic term in regression

I have the following linear regression: import statsmodels.formula.api as sm model = sm.ols(formula = 'a ~ b + c', data = …

python regression statsmodels quadratic
Python scikits - Buffer has wrong number of dimensions (expected 1, got 2)

I am trying this code snippet. I am using scikits.learn 0.8.1 from scikits.learn import linear_model import numpy as …

python numpy regression scikits scikit-learn