Mathematical and Statistical Estimation Approaches in Epidemiology
An inverse problem statistical methodology summary
Publication
, Chapter
Banks, HT; Davidian, M; Samuels, JR; Sutton, KL
December 1, 2009
We discuss statistical and computational aspects of inverse or parameter estimation problems for deterministic dynamical systems 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 illustrated throughout with the popular logistic growth model of Verhulst and Pearl as well as with a recently developed population level model of pneumococcal disease spread. © 2009 Springer Netherlands.
Duke Scholars
DOI
ISBN
9789048123124
Publication Date
December 1, 2009
Start / End Page
249 / 302
Citation
APA
Chicago
ICMJE
MLA
NLM
Banks, H. T., Davidian, M., Samuels, J. R., & Sutton, K. L. (2009). An inverse problem statistical methodology summary. In Mathematical and Statistical Estimation Approaches in Epidemiology (pp. 249–302). https://doi.org/10.1007/978-90-481-2313-1_11
Banks, H. T., M. Davidian, J. R. Samuels, and K. L. Sutton. “An inverse problem statistical methodology summary.” In Mathematical and Statistical Estimation Approaches in Epidemiology, 249–302, 2009. https://doi.org/10.1007/978-90-481-2313-1_11.
Banks HT, Davidian M, Samuels JR, Sutton KL. An inverse problem statistical methodology summary. In: Mathematical and Statistical Estimation Approaches in Epidemiology. 2009. p. 249–302.
Banks, H. T., et al. “An inverse problem statistical methodology summary.” Mathematical and Statistical Estimation Approaches in Epidemiology, 2009, pp. 249–302. Scopus, doi:10.1007/978-90-481-2313-1_11.
Banks HT, Davidian M, Samuels JR, Sutton KL. An inverse problem statistical methodology summary. Mathematical and Statistical Estimation Approaches in Epidemiology. 2009. p. 249–302.
DOI
ISBN
9789048123124
Publication Date
December 1, 2009
Start / End Page
249 / 302