Parameter Estimation in Engineering and ScienceIntroduction to and survey of parameter estimation; Probability; Introduction to statistics; Parameter estimation methods; Introduction to linear estimation; Matrix analysis for linear parameter estimation; Minimization of sum of squares functions for models nonlinear in parameters; Design of optimal experiments. |
Contents
Introduction to and Survey of Parameter Estimation | 1 |
1 | 10 |
3 | 20 |
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Parameter Estimation in Engineering and Science James Vere Beck,Kenneth J. Arnold Limited preview - 1977 |
Common terms and phrases
analysis approximate assumed B₁ B₂ Bayes's theorem Box-Kanemasu calculated confidence interval confidence region considered constraints continuous random variable correlated covariance matrix criterion degrees of freedom dependent variable derivative diagonal differential equation distribution function equal to zero example expected value Gauss method H₂ heat Hence independent observations inverse iteration known large number MAP estimation maximized maximum likelihood estimation measurement errors median ML estimation n₁ nonlinear normal distribution obtained ordinary least squares parameter estimation parameter vector possible values prior distribution prior information probability density function procedure regression residuals sample space Section sensitivity coefficients sensors sequential shown in Fig Solution squares function ẞ₁ ẞ₂ standard assumptions standard deviation statistic sum of squares symmetric t₁ temperature theorem tion unbiased estimator X₁ Y₁ zero mean