I am trying to recreate this plot from this website in Python instead of R: Background I have a dataframe called boston (the popular educational boston housing dataset). I created a multiple linear regression model with some variables with statsmodels api below. Everything works. I create a dataframe of actual values from the boston dataset and predicted values from above

# Tag: statsmodels

## RFE from scikit-learn feature_selection with NegativeBinomial from statsmodels as estimator

I’m trying to use RFE from scikit-learn with an estimator from statsmodels NegativeBinomial. So I created my own class: But I get this error: Does someone has an idea? Answer You can modify your code to require endog and exog variables, instead of using the formula API:

## freq parameter not presented in seasonal_decompose function

let us suppose we have following code : result of dataframe is given below : also it returns following error : instead i know that there is keyword period, are they same?generally we know that period is 1/frequency, but in this case how should i define period? or how can i create frequency index? please help me Answer The period

## How to do test of equality of coefficient for 2SLS in Statsmodels or Linearmodels?

So if I ran an experiment with multiple treatment groups and a control, I would analyse the results using Statsmodel ols to see if any of the treatment group were statistically different from the control group: y ~ C(treatment_group, Treatment(‘Control’) I would then run results.t_test_pairwise() to find out if the coefficients of each treatment group were equal. I.e. to know

## Initialising Model in Python’s statsmodels

I am having difficulties understanding how to initialise an empty as well as as a known initial config model in statsmodels, here imported as I get the following error: I have has similar experiences with the method: On the User Guide, it does not give any inputs to this method so I do not know the syntax needed to initialise

## How to do Linear Regression and get Standard Deviation (Python)

I have this very simple problem, but somehow I have not found a solution for it yet: I have two curves, A1 = [1,2,3] A2 = [4,5,6] I want to fit those curves to another curve B1 = [4,5,3] with Linear Regression so B1 = aA1 + bA2 This can easily be done with sklearn LinearRegression – but sklearn does

## Python statsmodels – ValueError: how to create variable in range 0 to 1?

Code: The problem I have is with the “You will need to create a new variable from baths, and it should make it such that those observations of 1 bath correspond to a value of 0, and those with more than 1 bath correspond to a 1.” instruction. I really do not know how to do that. I know that

## Two parameter non-linear function for modeling a 3-D surface

I’m interested in modeling this surface with a simple equation that takes in two parameters (x,y) values and produces a z value. Ideally an equation that has a simple form. I have tried Monkey Saddle, polynomial regression (3rd and 4th order) and also multi-linear and log-linear OLS with some success (R^2 0.99), but none that are perfect especially for the

## How do you get the adjusted R-squared for the test data in statsModels?

I have a dataset like and I built the linear model for the train data Now what I want to do is get the adjusted R^2 value based on the test data. Is there a simple command for this? I’ve been trying to build it from scratch and keep getting an error. What I’ve been trying: but it complains about

## How to forecast out of sample with AutoRegression from statsmodel?

I have time-series sales data. First I group-by the sales by a year. Than I want to forecast the sales for the years 2021,2022 and 2023. I have data from the year 2000. My question is similar to this one, however I want an answer on how to make forecast outside of the training index. If I do this the