13Process Modeling Through Regression Analysis

  1. 13-1 Introduction and chapter objectives
  2. 13-2 Deterministic and probabilistic models
  3. 13-3 Model assumptions
  4. 13-4 Least squares method for parameter estimation
  5. 13-5 Model validation and remedial measures
  6. 13-6 Estimation and inferences from a regression model
  7. 13-7 Qualitative independent variables
  8. 13-8 Issues in multiple regression
  9. 13-9 Logistic regression Summary
  10. Summary
X i Yβ i imgimgimgnpR 2 Independent variableDependent variableParameters of regression modelRandom error componentPredicted valueEstimated model coefficientNumber of observationsNumber of independent variables + 1Coefficient of determination imge i DWSσ 2s 2h i D i Adjusted coefficient of determinationResidualDurbin–Watson statisticWorking–Hotelling coefficientScheffé coefficientVariance of error componentEstimated variance of error componentLeverage coefficientCook's distance

13-1 Introduction and Chapter Objectives

It is often of interest to determine the nature of the impact of process variables on some output quality characteristic. Such analyses ...

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