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A simplex procedure for fitting nonlinear pharmacokinetic models

✍ Scribed by Jerold S. Harmatz; David J. Greenblatt

Publisher
Elsevier Science
Year
1987
Tongue
English
Weight
726 KB
Volume
17
Category
Article
ISSN
0010-4825

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✦ Synopsis

A convenient and readily modifiable nonlinear regression procedure, based on two Pascal programs, is described. This procedure, suitable for running on both microcomputers and mainframes, is presented as utilized in ongoing clinical pharmacokinetic work. One program uses the simplex algorithm to fit data conforming to any of six models of drug disposition. In addition to the regression terms, it generates logarithmic plots of the function and calculates derived kinetic variables of drug distribution, elimination and clearance. This program is driven by another which batches together required data and parameter information to build a control file for solving multiple curve-fitting problems.

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## Abstract Forecasting for nonlinear time series is an important topic in time series analysis. Existing numerical algorithms for multi‐step‐ahead forecasting ignore accuracy checking, alternative Monte Carlo methods are also computationally very demanding and their accuracy is difficult to contro