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VII. Observation-Parameter Statistics

VII. Observation-Parameter Statistics

VII. Observation-Parameter Statistics. Composite scaled sensitivities for estimated parameters Parameter variances and covariances Leverage and Influence Parameter correlation coefficients Parameter uniqueness Parameter standard deviations, confidence intervals, and coefficients of variation

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554 views • 35 slides
VII. Observation-Parameter Statistics

VII. Observation-Parameter Statistics

VII. Observation-Parameter Statistics. Composite scaled sensitivities for estimated parameters Parameter variances and covariances Leverage and Influence Parameter correlation coefficients Parameter uniqueness Parameter standard deviations, confidence intervals, and coefficients of variation

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516 views • 35 slides
VII. Observation-Parameter Statistics

VII. Observation-Parameter Statistics

VII. Observation-Parameter Statistics. Composite scaled sensitivities for estimated parameters Parameter variances and covariances Leverage and Influence Parameter correlation coefficients Parameter uniqueness Parameter standard deviations, confidence intervals, and coefficients of variation

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353 views • 35 slides
VIII: Methods for Evaluating Model Predictions

VIII: Methods for Evaluating Model Predictions

VIII: Methods for Evaluating Model Predictions. 1. Define predictive quantity and calculate sensitivities and standard deviations (Ex8.1a) 2. Assess data needs for the predictions Which parameters are important to predictions?

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406 views • 24 slides
Calibration Guidelines

Calibration Guidelines

Calibration Guidelines. Model development. Model testing. 9. Evaluate model fit 10. Evaluate optimal parameter values 11. Identify new data to improve parameter estimates 12. Identify new data to improve predictions 13. Use deterministic methods 14. Use statistical methods.

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309 views • 23 slides
Calibration Guidelines

Calibration Guidelines

Calibration Guidelines. Model development. Model testing. 9. Evaluate model fit 10. Evaluate optimal parameter values 11. Identify new data to improve parameter estimates 12. Identify new data to improve predictions 13. Use deterministic methods 14. Use statistical methods.

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312 views • 23 slides

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