Results 261 to 270 of about 1,779,788 (319)

Biased Estimators and Unstable Betas

The Journal of Finance, 1980
STUDIES [1, 2, 3, 5, 8, 10] ESTIMATING AND ANALYZING the stability of security betas have theoretical and practical implications. The measurement of pure, or systematic, risk of securities is important in portfolio selection and in applications of the Capital Asset Pricing Model (CAPM).
Scott, Elton, Brown, Stewart
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Administrative Records Mask Racially Biased Policing—CORRIGENDUM

American Political Science Review, 2020
Researchers often lack the necessary data to credibly estimate racial discrimination in policing. In particular, police administrative records lack information on civilians police observe but do not investigate.
D. Knox, Will Lowe, Jonathan Mummolo
semanticscholar   +1 more source

Doubly Robust Estimator for Ranking Metrics with Post-Click Conversions

ACM Conference on Recommender Systems, 2020
Post-click conversion, a pre-defined action on a web service after a click, is an essential form of feedback, as it directly contributes to the final revenue and accurately captures user preferences for items, compared with the ambiguous click.
Yuta Saito
semanticscholar   +1 more source

Estimating Chlorophyll Extraction Biases

Journal of the Fisheries Research Board of Canada, 1979
A simplified chlorophyll analytical procedure is described that requires 4 min/sample and features an overall precision (measured by the coefficient of variation, C.V.) of ~ 3% at the 15 mg/m3 chlorophyll a level. The C.V. varies inversely with concentration for spectrophotometric determinations.
R. E. Stauffer, G. F. Lee, David E. Armstrong   +2 more
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A new Liu-type estimator in binary logistic regression models

Communications in Statistics - Theory and Methods, 2020
In logistic regression models, the maximum likelihood method is commonly used to estimate the model parameters. However, unstable parameter estimates are obtained as a result of multicollinearity.
Esra Ertan, K. Akay
semanticscholar   +1 more source

Biased estimates of nonrenal clearance

Journal of Pharmaceutical Sciences, 2001
The goal of the investigation was to critically evaluate published values for oral nonrenal clearance and their postulated dependence on renal function with drugs administered orally to subjects with varying renal function. Derivation of the pertinent equations indicated that the values reported for oral nonrenal clearance tend to systematically ...
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Topological Estimation Biases with Covarion Evolution

Journal of Molecular Evolution, 2007
Covarion processes allow changes in evolutionary rates at sites along the branches of a phylogenetic tree. Covarion-like evolution is increasingly recognized as an important mode of protein evolution. Several recent reports suggest that maximum likelihood estimation employing covarion models may support different optimal topologies than estimation ...
Huai-Chun, Wang, Edward, Susko, Matthew, Spencer, Andrew J, Roger   +3 more
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Pseudoscore‐based estimation from biased observations

Statistics in Medicine, 2006
AbstractThere are many practical situations where observation of the primary variableYfor individuals in a population is incomplete and depends on some auxiliary variablesXthat are potentially correlated withY. We consider parameter estimation for the distribution ofYwith the incomplete data, without specifying the underlying association betweenYandX ...
X Joan, Hu, R Jason, Schroeder, Winfred C, Wang, James M, Boyett   +3 more
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Liu-type estimator for the gamma regression model

Communications in statistics. Simulation and computation, 2018
In this paper, we propose a new biased estimator called Liu-type estimator in gamma regression models in the presence of collinearity. We also consider some other estimators such as ridge estimator and Liu estimator and conduct a Monte Carlo simulation ...
Z. Algamal, Yasin Asar
semanticscholar   +1 more source

Chapter 10 Biased estimation

1983
Publisher Summary This chapter presents the conventional linear-statistical models, estimators, and hypothesis testing framework. Sampling theory and Bayes estimators that permit sample information and various types of nonsample information are specified and evaluated.
G.G. Judge, M.E. Bock
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