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Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

1 vote

How to make a regression with two explicative variables and interpret the results

This can be a good start for the multivariate regression. First of all, you need a mathematical model like this: $y = \beta_0 + \beta_1 X_1 + \beta_2 X_2 + \varepsilon$. …
Enzo D'Innocenzo's user avatar
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Is there a way to get an r-squared value for nonlinear regression line?

You can obtain an estimate of $R^2$ for non linear regression by calculate the square of the correlation value between the fitted values and the real values of the response variable. …
Enzo D'Innocenzo's user avatar
0 votes

Validation of modeling step of PLS

By using the PLS Regression, you can follow these steps: Apply the algorithm by using a validation method (I recommend the full cross validation); Select the number of latent variables that the validation …
Enzo D'Innocenzo's user avatar
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Normality of Residuals

No, because every time you build a model, you must test the normal distribution and the zero mean of the residuals. So, in your case, if you drop a variable of the first model you must re-test the nor …
Enzo D'Innocenzo's user avatar