Modeling abilities in 3-IRT models.
Cepeda Cuervo, Edilberto, Peláez Andrade, José Manuel (2004)
Revista Colombiana de Estadística
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Cepeda Cuervo, Edilberto, Peláez Andrade, José Manuel (2004)
Revista Colombiana de Estadística
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Wojciech Niemiro (1995)
Applicationes Mathematicae
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Statistical inference procedures based on least absolute deviations involve estimates of a matrix which plays the role of a multivariate nuisance parameter. To estimate this matrix, we use kernel smoothing. We show consistency and obtain bounds on the rate of convergence.
Rydlewski, Jerzy P. (2007)
Zeszyty Naukowe Uniwersytetu Jagiellońskiego. Universitatis Iagellonicae Acta Mathematica
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Anna Czapkiewicz (1999)
Applicationes Mathematicae
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We discuss some methods of estimation in bivariate errors-in-variables linear models. We also suggest a method of constructing consistent estimators in the case when the error disturbances have the normal distribution with unknown parameters. It is based on the theory of estimating variance components in linear models. A simulation study is presented which compares this estimator with the maximum likelihood one.
Atanasiu, Virginia (2008)
APPS. Applied Sciences
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Yadlin A., Marisa (2000)
Journal of Applied Mathematics and Decision Sciences
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Sarhan, Ammar M., Zaindin, Mazen (2009)
APPS. Applied Sciences
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Wojciech Niemiro (1993)
Applicationes Mathematicae
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We consider the empirical risk function (for iid ’s) under the assumption that f(α,z) is convex with respect to α. Asymptotics of the minimum of is investigated. Tests for linear hypotheses are derived. Our results generalize some of those concerning LAD estimators and related tests.
Wong, Wing-Keung, Bian, Guorui (2000)
Journal of Applied Mathematics and Decision Sciences
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Alicja Jokiel-Rokita (1998)
Applicationes Mathematicae
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A problem of minimax prediction for the multinomial and multivariate hypergeometric distribution is considered. A class of minimax predictors is determined for estimating linear combinations of the unknown parameter and the random variable having the multinomial or the multivariate hypergeometric distribution.
Roşca, Natalia C. (2009)
Acta Universitatis Apulensis. Mathematics - Informatics
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Ristić, Miroslav, Popović, Biljana Č. (2004)
Novi Sad Journal of Mathematics
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