Regression in R
R
How to Perform a Breusch-Godfrey Test in R
One of the key assumptions in linear regression is that there is no correlation between the residuals, e.g. the residuals are independent.
To test for...
R
How to Perform Robust Regression in R (Step-by-Step)
Robust regression is a method we can use as an alternative to ordinary least squares regression when there are outliers or influential observations in...
R
How to Predict a Single Value Using a Regression Model in R
To fit a linear regression model in R, we can use the lm() function, which uses the following syntax:
model
We can then use the...
R
How to Create a Confusion Matrix in R (Step-by-Step)
Logistic regression is a type of regression we can use when the response variable is binary.
One common way to evaluate the quality of a...
R
How to Perform Power Regression in R (Step-by-Step)
Power regression is a type of non-linear regression that takes on the following form:
y = axb
where:
y: The response variable
x: The predictor variable
a, b: The...
R
The Difference Between glm and lm in R
The programming language R offers the following functions for fitting linear models:
1. lm – Used to fit linear models
This function uses the following syntax:
lm(formula,...
R
How to Use the predict function with glm in R (With Examples)
The glm() function in R can be used to fit generalized linear models. This function is particularly useful for fitting logistic regression models, Poisson...
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