when using the .summary() function using pandas statsmodels, the OLS Regression Results include the following fields. coef std err t P>|t| [0.025 0.975] How can I get the standardised coeffic...

I am trying to understand how the best coefficients are calculated in a logistic regression cross-validation, where the "refit" parameter is True. If I understand the docs correctly, the best coef...

I want to create a polynomial ring which has float Coefficients like this. I can create with integers but, Floats does not work. using Oscar S, (a,b,c,d) = PolynomialRing(QQ,["a","b...

Using Python 3.10.0 and NumPy 1.21.4. I'm trying to understand why Polynomial.fit() calculates wildly different coefficient values from polyfit(). In the following code: import numpy as np def mai...

I'm trying to get the coefficients of a numpy.polynomial.polynomial.Polynomial obtained via the fit method: import numpy.polynomial as poly x = [1, 2, 3, 4, 5] y = [16, 42.25, 81, 132.25, 196] c ...

I have fit a logistic regression model to my data. Imagine, I have four features: 1) which condition the participant received, 2) whether the participant had any prior knowledge/background about th...

I am using following code with glmnet: > library(glmnet) > fit = glmnet(as.matrix(mtcars[-1]), mtcars[,1]) > plot(fit, xvar='lambda') However, I want to print out the coefficients at...

I want to compare the results of different models (lm, glm, plm, pglm) in a table in R using stargazer or a similar tool. However I can't find a way to display the coefficients in scientific notati...

I would like to perform Deming regression (or any equivalent of a regression method with uncertainties in both X and Y variables, such as York regression). In my application, I have a very good sci...

I am using a Logistic Regression (in scikit) for a binary classification problem, and am interested in being able to explain each individual prediction. To be more precise, I'm interested in predic...

I have a problem with glm function in R. Specifically, I am not sure how to include nominal variables. The results that I get in R after running the glm function are the following: > df x1 ...

I am a little new to this. I am using a simple Logistic Regression Classifier in python scikit-learn. I have 4 features. My code is X_train, X_test, y_train, y_test = train_test_split(X, Y, tes...

My question is about the unnecessary predictors, namely the variables that do not provide any new linear information or the variables that are linear combinations of the other predictors. As you ca...

How could I extract coefficients (b0 and b1) with their respectively standard errors for each experimental unit (plot )in a linear mixed model such as this one: Better fits for a linear model wi...

I am currently using Scikit-Learn's LogisticRegression to build a model. I have used from sklearn import preprocessing scaler=preprocessing.StandardScaler().fit(build) build_scaled = scaler.trans...

numpy.polynomial.polynomial.Polynomial stores polynomial coefficients in order of increasing degree, while numpy.poly1d stores polynomial coefficients in order of decreasing degree. Is there a rea...

A) I am interested in the effects of a continuous variable (Var1) on a continuous dependent variable (DV) conditional on four different groups, which are defined by two bivariate variables (Dummy1 ...

Is there a built-in function in maxima to get from a polynomial function a list with its coefficients? And to get the degree of the polynomial? The most similar function I found is args, but it al...

I am trying to extract intercepts and slopes for 500 variables from a qplot. The code I am using: qplot(gd, nd, data = test, colour = factor(ENT)) + geom_smooth(method = "lm", se = FALSE) Coul...

I used to use the code below to calculate standardized coefficients of a lmer model. However, with the new version of lme the structure of the returned object has changed. How to adapt the functi...

I want to extract the standard errors from a list of logistic regression models. This is the logistic regression function, designed this way so i can run more than one analysis at once: glmfunk &...