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Linear Regression Models Under Multicollinearity

Om Linear Regression Models Under Multicollinearity

This book proposes the various types of new Ridge regression estimators to deal with the problem of multicollinearity in multiple linear regression analysis.An Ordinary ridge regression estimators and an orthonormal( ridge regression estimators have been derived by selecting the values for ridge parameter based on studentized residuals.A partitioned linear regression model has been specified and the ridge regression estimator has been developed by using Internally studentized residual sum of squares.besides these,an Adaptive General Ridge regression estimator's and a new combined restricted ridge regression estimators have been proposed along with iterative procedures for the solutions of elements of ridge parameters matrix.

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  • Språk:
  • Engelsk
  • ISBN:
  • 9783659389764
  • Bindende:
  • Paperback
  • Sider:
  • 216
  • Utgitt:
  • 24. juli 2013
  • Dimensjoner:
  • 229x152x12 mm.
  • Vekt:
  • 322 g.
  Gratis frakt
Leveringstid: 2-4 uker
Forventet levering: 27. desember 2024
Utvidet returrett til 31. januar 2025

Beskrivelse av Linear Regression Models Under Multicollinearity

This book proposes the various types of new Ridge regression estimators to deal with the problem of multicollinearity in multiple linear regression analysis.An Ordinary ridge regression estimators and an orthonormal( ridge regression estimators have been derived by selecting the values for ridge parameter based on studentized residuals.A partitioned linear regression model has been specified and the ridge regression estimator has been developed by using Internally studentized residual sum of squares.besides these,an Adaptive General Ridge regression estimator's and a new combined restricted ridge regression estimators have been proposed along with iterative procedures for the solutions of elements of ridge parameters matrix.

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