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Original Articles

An Empirical Study of Jackknife-Constructed Confidence Regions in Nonlinear Regression

Pages 123-129 | Published online: 09 Apr 2012

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Peiliang Xu & Seiichi Shimada. (2000) Least squares parameter estimation in multiplicative noise models. Communications in Statistics - Simulation and Computation 29:1, pages 83-96.
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Hui Quan & Wei-yann Tsai. (1992) Jackknife for the proportional hazards model. Journal of Statistical Computation and Simulation 43:3-4, pages 163-176.
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Jeffrey S. Simonoff & Chih-Ling Tsai. (1988) Jackknifing and bootstrapping quasi–likelihood estimators. Journal of Statistical Computation and Simulation 30:3, pages 213-232.
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JanetR. Donaldson & RobertB. Schnabel. (1987) Computational Experience With Confidence Regions and Confidence Intervals for Nonlinear Least Squares. Technometrics 29:1, pages 67-82.
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JeffreyS. Simonoff & Chih-Ling Tsai. (1986) Jackknife-Based Estimators and Confidence Regions in Nonlinear Regression. Technometrics 28:2, pages 103-112.
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Terry Fox, David Hinkley & Kinley Larntz. (1980) Jackknifing in Nonlinear Regression. Technometrics 22:1, pages 29-33.
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Gabriel C. Motta-Ribeiro, Marcos F. Vidal Melo & Frederico C. Jandre. (2019) A simplified 4-parameter model of volumetric capnograms improves calculations of airway dead space and slope of Phase III. Journal of Clinical Monitoring and Computing 34:6, pages 1265-1274.
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Yiren Yuan, Makoto Uyeshima, Qinghua Huang, Ji Tang, Qi Li & Yuntian Teng. (2020) Continental-scale deep electrical resistivity structure beneath China. Tectonophysics 790, pages 228559.
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Özlem Türkşen. (2020) Obtaining interval estimates of nonlinear model parameters based on combined soft computing tools. Journal of Intelligent & Fuzzy Systems 38:1, pages 609-618.
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Kurex SidikJeffrey N. Jonkman. (2016) A comparison of the variance estimation methods for heteroscedastic nonlinear models. Statistics in Medicine 35:26, pages 4856-4874.
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Héla Jaziri, Widien Khoufi & Sadok Ben Meriem. (2015) Assessment Approach of <i>Melicertus kerathurus</i> Stock along the North-Eastern Tunisian Coast Using a Surplus Production Model Incorporating Temperature Parameter. American Journal of Climate Change 04:05, pages 417-430.
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Constantinos V. Chrysikopoulos, Pin‐Yi Hsuan & Marios M. Fyrillas. (2002) Bootstrap estimation of the mass transfer coefficient of a dissolving nonaqueous phase liquid pool in porous media. Water Resources Research 38:3.
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P. Nikitas & A. Pappa-Louisi. (2000) Non-linear least-squares fitting with microsoft excel solver and related routines in HPLC modelling of retention. Chromatographia 52:7-8, pages 477-486.
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Brent E. SleepLynda J. Mulcahy. (1998) Estimation of Biokinetic Parameters for Unsaturated Soils. Journal of Environmental Engineering 124:10, pages 959-969.
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Andrew J. Myles, Alan F. Murray, A. Robin Wallace, John Barnard & Gordon Smith. (1997) Estimating MLP generalisation ability without a test set using fast, approximate leave-one-out cross-validation. Neural Computing & Applications 5:3, pages 134-151.
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SS Guo, WC Chumlea & DB Cockram. (1996) Use of statistical methods to estimate body composition. The American Journal of Clinical Nutrition 64:3, pages 428S-435S.
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I. S. Chan, A. A. Goldstein & J. B. Bassingthwaighte. (1993) SENSOP: A derivative-free solver for nonlinear least squares with sensitivity scaling. Annals of Biomedical Engineering 21:6, pages 621-631.
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Sheila Ards. (2016) Estimating Local Child Abuse. Evaluation Review 13:5, pages 484-515.
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S. Wold, A. Ruhe, H. Wold & W. J. Dunn, III. (1984) The Collinearity Problem in Linear Regression. The Partial Least Squares (PLS) Approach to Generalized Inverses. SIAM Journal on Scientific and Statistical Computing 5:3, pages 735-743.
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