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

0 votes
0 answers
406 views

Do Principal Component Analysis regression eliminate noise in the data set?

I am comparing the perfomance of PCA regression (i.e. regression where original regressors are replaced by few their pr. components) to that of regression with the original regressors in which I added … My question: Is it really possible to denoise independent variables with PCA-regression? If so, how should I proceed? …
gis20's user avatar
  • 131
0 votes
1 answer
380 views

Goodness of fit (r squared) for circular data

I have started to work with regression models for angular data. In particular with the package circular in R. …
gis20's user avatar
  • 131
1 vote
1 answer
7k views

It is correct to use r squared instead of r for correlation of 2 variables?

I have seen many reports and software in which the coefficient of determination $R^2$ is used instead of $r$ when describing the correlation of two variables before doing linear regression. … In my opinion $R^2$ should only be used to evaluate the goodness of fit after linear regression. …
gis20's user avatar
  • 131