Recipe 11.1, 'Regressing on Transformed Data', discusses transforming your variables into a (more) linear relationship so that you can use the well-developed machinery of linear regression. A simple linear regression is the most basic model.The locations are random points (X k, Y k) in the two-dimensional unit square x.
In the first example, the training set consists of n = 100 data points generated as follows. We did some simulations to compare the performance of simple regression versus linear regression. Case studies and Excel spreadsheet with computations. I have worked on a wide range of statistical problems ranging over air pollution, anxiety and depression, astronomy, athletics, concrete, cosmetics, flooding, fungicides, fuel filters, marketing of cars, obesity and schizophrenia. My research is on the interface between the theory and application of Statistics.
