Please use this identifier to cite or link to this item: http://hdl.handle.net/10316/5245
Title: Nonlinear regression in parameter estimation from polarographic signals
Authors: Pais, A. A. C. C. 
Pereira, J. L. G. C. 
Redinha, J. S. 
Keywords: Least-squares; Monte-Carlo; Bootstrap; Jackknife; Parameter estimation; Polarography
Issue Date: 2000
Citation: Computers & Chemistry. 24:3-4 (2000) 533-539
Abstract: In this work we describe a detailed treatment of polarographic data curves, including error analysis, by means of nonlinear least-squares in its standard form (or resorting to the errors in variables model). Error estimates for the related parameters are additionally verified by Monte-Carlo simulation and resampling techniques.
URI: http://hdl.handle.net/10316/5245
Rights: openAccess
Appears in Collections:FCTUC Química - Artigos em Revistas Internacionais

Files in This Item:
File Description SizeFormat
file7f861f9e36ed4b74884f34fa77a64c34.pdf113.76 kBAdobe PDFView/Open
Show full item record

Page view(s)

105
checked on Feb 12, 2020

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.