An Inverse Problem Statistical Methodology Summary

  title={An Inverse Problem Statistical Methodology Summary},
  author={Harvey Thomas Banks and M. Davidian and Judith R. Samuels},
We discuss statistical and computational aspects of inverse or parameter estimation problems based on Ordinary Least Squares and Generalized Least Squares with appropriate corresponding data noise assumptions of constant variance and nonconstant variance (relative error), respectively. Among the topics included here are mathematical model, statistical model and data assumptions, and some techniques (residual plots, sensitivity analysis, model comparison tests) for verifying these. The ideas are… CONTINUE READING


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Statistical methods for model comparison in parameter estimation problems for distributed systems

H. T. Banks, B. G. Fitzpatrick
CAMS Tech. Rep. 89-4, September, 1989, University of Southern California; J. Math. Biol., 28 • 1990
View 8 Excerpts
Highly Influenced

Nonlinear Regression

G.A.F. Seber, C. J. Wild
John Wiley & Sons, Inc., New York • 1989
View 4 Excerpts
Highly Influenced

Transformation and Weighting in Regression

R. J. Carroll, D. Ruppert
Chapman and Hall, New York • 1988
View 3 Excerpts
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Ernstberger and S.L.Grove, Standard errors and confidence intervals in inverse problems: sensitivity and associated pitfalls

S.L.H.T. Banks
CRSC-TR06-10, March, • 2006
View 2 Excerpts

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