👉 The word "Alternating Least Squares Predicting R Test" confuses me.
In statistics, it's a type of non-parametric test that uses linear regression models to predict responses based on different levels of explanatory variables in the model. This method allows you to analyze how well your hypothesis is being tested and whether the changes in response are due to noise or other factors.
The 'Conf' part suggests it might be a confidence interval, which can provide a sense of statistical power.
The word "Alternating Least Squares" refers to this concept where different levels of explanatory variables are used in the regression model. The term "Least Squares" means minimizing error over all possible values of the independent variable (X) by using a linear function, which is typically y = ax + b, where 'a' and 'b' are coefficients.
The word 'Predicting' refers to an aspect of this test in which you're testing whether your model fits your data better than the simple least squares regression. The term 'R Test' often refers to the robust linear regression (R-LR) method.
So, it's a statistical technique that helps determine how well different levels of explanatory variables are explaining the response variable, as opposed to using a single predictor directly and thus predicting the entire response.
Remember, this might be a bit obscure.
AlternatingLeastSquaresPredictingRTest.conf