Results 271 to 280 of about 1,818,251 (309)
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Boundary Bias Correction for Nonparametric Deconvolution
Annals of the Institute of Statistical Mathematics, 2000zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhang, Shunpu, Karunamuni, Rohana J.
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Error-Correcting Output Coding Corrects Bias and Variance
1995Previous research has shown that a technique called error-correcting output coding (ECOC) can dramatically improve the classification accuracy of supervised learning algorithms that learn to classify data points into one of k ≫ 2 classes. This paper presents an investigation of why the ECOC technique works, particularly when employed with decision-tree
Eun Bae Kong, Thomas G. Dietterich
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Bias and Bias Correction in Fish Recruitment Prediction
North American Journal of Fisheries Management, 2004Abstract A lognormal error is usually assumed in the traditional stock–recruitment (SR) analysis. In this paper, I demonstrate that a positive bias results when an SR model with lognormal error is used for fish recruitment prediction. Not only is this bias exponentially dependent on the structure of the model's residual variance and the ...
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A Least Squares Correction for Selectivity Bias
Econometrica, 1980WHEN ESTIMATING REGRESSION MODELS it is very nearly always assumed that the sample is random. The recent literature has begun to deal with the problems which arise when estimating a regression model with samples which may not be random. The most general case in which one only has access to a single nonrandom sample has not been addressed since it is a ...
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1984
A non-linear correction function K(Z*) is proposed to transform any initial linear estimator Z* into a conditionally unbiased estimator Z** = K(Z*) with reduced conditional estimation variance. The correction is based upon an isofactorial representation of the bivariate distribution of the true grade Z and Z*; it is designed to deal with the problems ...
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A non-linear correction function K(Z*) is proposed to transform any initial linear estimator Z* into a conditionally unbiased estimator Z** = K(Z*) with reduced conditional estimation variance. The correction is based upon an isofactorial representation of the bivariate distribution of the true grade Z and Z*; it is designed to deal with the problems ...
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An easily correctable bias in BMI
The American Journal of the Medical Sciences, 2022openaire +2 more sources
Bias correction of high resolution regional climate model data
Journal of Hydrology, 2012Hendrik Feldmann, H -J Panitz
exaly