Top "Linear-regression" questions

for issues related to linear regression modelling approach

matrices are not aligned Error: Python SciPy fmin_bfgs

Problem Synopsis: When attempting to use the scipy.optimize.fmin_bfgs minimization (optimization) function, the function throws a derphi0 = np.…

python-3.x scipy linear-algebra linear-regression
Linear regression slope error in numpy

I use numpy.polyfit to get a linear regression: coeffs = np.polyfit(x, y, 1). What is the best way to …

numpy linear-regression standard-deviation
How to use formula in R to exclude main effect but retain interaction

I do not want main effect because it is collinear with a finer factor fixed effect, so it is annoying …

r regression linear-regression lm categorical-data
Multiple Linear Regression in Power BI

Suppose I have a set of returns and I want to compute its beta values versus different market indices. Let's …

excel-formula linear-regression powerbi dax
Multiple Regression in Math.Net Numerics

I achieved simple single regression using math.net regression method like this: var xdata = new double[] { 10, 20, 30, 40, 50 }; var ydata = new double[] { 15, 20, 25, 55, 95 }; …

c# linear-regression math.net mathnet-numerics
Fitting Markov Switching Models to data in R

I'm trying to fit two kinds of Markov Switching Models to a time series of log-returns using the package MSwM …

r time-series linear-regression data-fitting markov-models
How to check interaction effects for a lot of predictors in R

I am trying to fit a regression model in R, after figuring out the main predictors, I want to check …

r linear-regression interaction
Predicting standard errors of forecast

I'm a newbie to R, coming from the Stata world. I've just run a linear model (with approx 100 variables, each …

r stata linear-regression forecasting standard-error
R: Dynamic linear regression with dynlm package, how to predict()?

I am trying to build a dynamic regression model and so far I did it with the dynlm package. Basically …

r dynamic linear-regression predict
R: Making sense of the output of a MCMCglmm

I performed a MCMCglmm (MCMCglmm package). Here is the summary of this model Iterations = 3001:12991 Thinning interval = 10 Sample size = 1000 DIC: 211.0108 G-structure: ~…

r statistics linear-regression bayesian