Category "regression"

Fixed effect instrumental variable (IV) regression with available diagnostic tests

May I please know an R package and code to run fixed effect instrumental variable (IV) regression with available diagnostic tests (e.g., weak instrument test, e

Name 'model' is not defined

When I input this code print(cross_val_score(model, X, y, cv=3)) An error comes back that reads name 'model' is not defined: print(cross_val_score(model, X, y

how can I turn my linear regression model from univariate into the multvariate?

I have built this univariate linear regression model from scratch and I am conceptually ok with how the multivariate version of it works. the problem is that ho

Finding the best linear section of data

I have some scientific data and wish to find the best region to fit a straight line in. Theoretically, the data should have a constant gradient but other influe

Predict on test data, using plm package in R, and calculate RMSE for test data

I built a model, using plm package. The sample dataset is here. I am trying to predict on test data and calculate metrics. # Import package library(plm) library

How to interpret MSE in Keras Regressor

I am trying to build a model to predict house prices. I have some features X (no. of bathrooms , etc.) and target Y (ranging around $300,000 to $800,000) I have

Converting categorical data into numerical values

I have a dataset with a lot of categorical mixed with numerical. I am trying to run a regression about obesity where the variables I'm trying to include are sta

How to interpret interactions in a multinomial ordinal regression (r)

A colleague and I ran a multinomial logistic regression using the 'ordinal' package in r and I am not sure how to interpret interactions between variables with

Decision tree regression code, when run shows only 'random_state = 0' and nothing else

I have taken a house price dataset. I have run the following code: import pandas as pd import numpy as np import matplotlib.pyplot as plt import seaborn as sns

Stargazer(): Create covariate labels with exponent?

I want to use stargazer() to create a table of the coefficients of three regressions. I have to rename the independent variables of the regressions and the vari

Issue with the prediction error plot using the yellowbrick library (regression)

I have three models for regression: linear regression: using ols_regressor = sm.OLS() random forest: using rf = RandomForestRegressor() artificial neural networ

regression analysis in brand funnel

What regression can I use for brand funnel? The participants who do not choose a brand in the consideration, can not pick the brand in the con

Predicted values for conditional logistic regression greater than 1

I have a multivariate conditional logistic regression model. Case and controls are matched on a 1 to many basis. I want to make predictions using the model. How

How can I get the history of the KerasRegressor?

I want to get KerasRegressor history but all the time I get (...) object has no attribute 'History' ''' # Regression Example With Boston Dataset: Standardized a

How to get the names of factor levels corresponding to fixed effect regression coefficients for a GAM in R?

I have a gam in R (mgcv package) with 7 parameters, and one of them is a fixed effect with 30 levels (30 names). I want to analyse the regression coefficients f

Decision tree regression producing multiple lines

I'm trying to make a single variable regression using decision tree regression. However when I'm plotting the results. Multiple lines show in the plot just like

Problem with my code- Univariate regression plot not showing lines

this will sound very basic, but I cannot find the solution to this problem with my code. I did a univariate regression (regr1) between the 2 variables immigrate

Activation function on the hidden layers for Regression models in neural networks

I am trying to predict a single output value,y, using two input features. I read that regression models usually don't use any activation function, and even when

Creating a regression summary table with multiple regressions, adding 1 independent variable at a time (R/Python)

I would like to know, whether there is a pre-built function / package which does a simply OLS regression, by adding one independent variable from a pre-defined

Possible to call the "Regression Trend" tool in pine script?

TradingView has this convenient Regression Trend tool in its UI, which can generate the trend channel for a specified period of time. I'm trying to create a pin