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Variance function estimation for immunoassays
Computer Programs in Biomedicine, 1980A computer program is described which implements a recently described [1], modified likelihood method of determining an appropriate weighting function to use when fitting immunoassay dose-response curves. The relationship between the variance of the response and its mean value is assumed to have an exponential form, and the best fit to this model is ...
G M, Raab, R, Thompson, I, McKenzie
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On polynomial variance functions
Probability Theory and Related Fields, 1992zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bar-Lev, Shaul K. +2 more
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A GRAPHICAL DIAGNOSTIC FOR VARIANCE FUNCTIONS
Australian & New Zealand Journal of Statistics, 2007SummaryThis paper proposes diagnostic plots for regression variance functions. It shows how to extend graphical methodology that uses Bayesian sampling for checking the regression mean function to also check the variance function. Plots can be constructed quickly and easily for any model of interest.
Pardoe, Iain, Cook, R. Dennis
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LOCAL MEDIAN ESTIMATION OF VARIANCE FUNCTION
Acta Mathematica Scientia, 2004zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yang, Ying +3 more
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Variance weighting functions in radioimmunoassay calibration
American Journal of Physiology-Endocrinology and Metabolism, 1986Software packages for radioimmunoassay calibration assume that expected counting rate is a function of ligand dose. Previous studies have indicated that variances of counting rate are also related to dose, but the structure of individual assays does not permit precise estimation of counting rate variances at individual doses.
T W, Gettys, P M, Burrows, D M, Henricks
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Journal of Applied Statistics, 1990
Estimates of variance from samples depend strongly on extreme values. Incomplete variance functions may be used to explain the unreliability of variance estimates when the distribution is long-tailed.
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Estimates of variance from samples depend strongly on extreme values. Incomplete variance functions may be used to explain the unreliability of variance estimates when the distribution is long-tailed.
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Estimating Variance Functions in Developmental Toxicity Studies
Biometrics, 1995The presence of intralitter correlation is a well known issue for analysis of the developmental toxicology data. The intralitter correlation coefficients observed in developmental toxicology data are generally different across dose groups. In this paper we use a generalized estimating equation procedure to model jointly the mean parameters and the ...
Bowman, Dale +2 more
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Fermi convolution and variance function
Proceedings of the Romanian Academy, Series A: Mathematics, Physics, Technical Sciences, Information Science, 2023In this paper, we determine the effect of the Fermi convolution power on the variance function of a Cauchy-Stieltjes Kernel (CSK) family. We then use the criteria of convergence for a sequence of variance functions to give an approximation of elements of the CSK family generated by the Fermi Poisson distribution.
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Minimum-variance synthetic discriminant functions
Journal of the Optical Society of America A, 1986The conventional synthetic discriminant functions (SDF’s) determine a filter matched to a linear combination of the available training images such that the resulting cross-correlation output is constant for all training images. We remove the constraint that the filter must be matched to a linear combination of training images and consider a general ...
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Kriging with Nonparametric Variance Function Estimation
1998A method for fitting regression models to data that exhibit spatial correlation and Heteroskedasticity is proposed. A combination of parametric and nonparametric regression techniques is used to iteratively estimate the various components of the model. The approach is demonstrated on a large dataset of predicted nitrogen runoff from agricultural lands ...
Opsomer, Jean D. +9 more
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