Results 281 to 290 of about 599,650 (333)

Bias in Nonlinear Regression

Biometrika, 1986
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Cook, R. D., Tsai, C.-L., Wei, B. C.
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Residuals in Nonlinear Regression

Biometrika, 1985
Abstract : The authors employ a quadratic expansion to investigate the behavior of the ordinary residuals in nonlinear regression. In particular, they derive quadratic approximations for the mean and variance of the ordinary residuals, and the covariances between the ordinary residuals and the fitted values.
R. D. COOK, CHIH-LING TSAI
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Nonlinear Regression with Dependent Observations

Econometrica, 1984
The authors establish general conditions for consistency and asymptotic normality for the nonlinear least squares estimators. These results are based on the extensions of the law of large numbers and the central limit theorem for random processes with mixing conditions.
White, Halbert, Domowitz, Ian
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Nonlinear regression: a hybrid model

Computers & Operations Research, 1999
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Nonlinear Regression Analysis of the Joint-Regression Model

Biometrics, 1997
Summary: The joint-regression model for two-way data assumes a linear relation between a continuous response and column effects. Standard methods for fitting the model condition on estimates of the column effects, but including column effects as covariates in the model results in a nonlinear estimation problem.
Ng, Meei Pyng, Grunwald, Gary K.
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A Continuation Method for Nonlinear Regression

SIAM Journal on Numerical Analysis, 1981
Many iterative regression methods only perform well near a solution.One may construct a modified problem with a free parameter $(k)$, which has a known solution for a particular k. By suitably deforming this problem through k-space one may, always remaining close to an intermediate solution, eventually solve the original problem.The continuation method
De Villiers, Noel, Glasser, David
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On nonlinear beta regression residuals

Biometrical Journal, 2017
We proposed a new residual to be used in linear and nonlinear beta regressions. Unlike the residuals that had already been proposed, the derivation of the new residual takes into account not only information relative to the estimation of the mean submodel but also takes into account information obtained from the precision submodel. This is an advantage
Espinheira, Patrícia L., Santos, Evelyne G., Cribari-Neto, Francisco   +2 more
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Nonlinear regression using spreadsheets

Trends in Pharmacological Sciences, 1995
Pharmacologists are often required to analyse nonlinear experimental effects by fitting the data to defined theoretical models. This may require a specialized computer program capable of performing nonlinear regression analysis, which can prove costly given the variety of pharmacological research.
W P, Bowen, J C, Jerman
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Nonlinear Regression With Variance Components

Journal of the American Statistical Association, 1992
Abstract The nonlinear model with variance components, which combines a nonlinear model for the mean with additive random effects, is applicable to split-plot and nested experiments. We propose two methods of estimation for the parameters of the nonlinear model for the mean: (1) estimated generalized least squares (EGLS), and (2) maximum likelihood ...
Marcia L. Gumpertz, Sastry G. Pantula
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Nonlinear Regression

Technometrics, 1991
Kenneth Berk, G. A. F. Seber, C. J. Wild
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