Application of Regularized Regressions to Identify Novel Predictors in Clinical Research (Original PDF from Publisher)

Original price was: $179.00.Current price is: $5.00.

By Ton J. Cleophas, Aeilko H. Zwinderman This textbook is an important novel menu for multiple variables regression entitled “regularized regression”. It is a must have for identifying unidentified leading factors. Also, you get fitted parameters for your overfitted data. Finally, there is no more need for commonly misunderstood p-values. Instead, the regression coefficient, R-value, as reported from a regression line has been applied as the key predictive estimator of the regression study. With simple one by one variable regression it is no wider than -1 to +1. With multiple variables regression it can easily get > +1 or Product…

Description

By Ton J. Cleophas, Aeilko H. Zwinderman

This textbook is an important novel menu for multiple variables regression entitled “regularized regression”. It is a must have for identifying unidentified leading factors. Also, you get fitted parameters for your overfitted data. Finally, there is no more need for commonly misunderstood p-values. Instead, the regression coefficient, R-value, as reported from a regression line has been applied as the key predictive estimator of the regression study. With simple one by one variable regression it is no wider than -1 to +1. With multiple variables regression it can easily get > +1 or

Product Details

  • Publisher ‏ : ‎ Springer; 2024th edition (December 21, 2024)
  • Language ‏ : ‎ English
  • Hardcover ‏ : ‎ 286 pages
  • ISBN-10 ‏ : ‎ 3031722469
  • ISBN-13 ‏ : ‎ 978-3031722462

Reviews

There are no reviews yet.

Be the first to review “Application of Regularized Regressions to Identify Novel Predictors in Clinical Research (Original PDF from Publisher)”

Your email address will not be published. Required fields are marked *