13Process Modeling Through Regression Analysis
- 13-1 Introduction and chapter objectives
- 13-2 Deterministic and probabilistic models
- 13-3 Model assumptions
- 13-4 Least squares method for parameter estimation
- 13-5 Model validation and remedial measures
- 13-6 Estimation and inferences from a regression model
- 13-7 Qualitative independent variables
- 13-8 Issues in multiple regression
- 13-9 Logistic regression Summary
- Summary
Symbols | |||
X i Yβ i npR 2 | Independent variableDependent variableParameters of regression modelRandom error componentPredicted valueEstimated model coefficientNumber of observationsNumber of independent variables + 1Coefficient of determination | e 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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