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pro vyhledávání: '"Kabaila, Paul"'
Autor:
Kabaila, Paul
The theory and computational methods for custom-made Gauss quadrature have been described in Gautschi's 2004 monograph. Gautschi has also provided Fortran and MATLAB code for the implementation and illustration of these methods. We have written an R
Externí odkaz:
http://arxiv.org/abs/2211.04729
Autor:
Kabaila, Paul, Ranathunga, Nishika
We consider a general regression model, without a scale parameter. Our aim is to construct a confidence interval for a scalar parameter of interest $\theta$ that utilizes the uncertain prior information that a distinct scalar parameter $\tau$ takes t
Externí odkaz:
http://arxiv.org/abs/2009.07464
Akademický článek
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Autor:
Kabaila, Paul1 (AUTHOR) P.Kabaila@latrobe.edu.au, Wijethunga, Christeen1 (AUTHOR)
Publikováno v:
Statistical Papers. May2024, Vol. 65 Issue 3, p1531-1551. 21p.
Autor:
Kabaila, Paul, Wijethunga, Christeen
Publikováno v:
Statistical Papers, 2023
Recently, Kabaila and Wijethunga assessed the performance of a confidence interval centred on a bootstrap smoothed estimator, with width proportional to an estimator of Efron's delta method approximation to the standard deviation of this estimator. T
Externí odkaz:
http://arxiv.org/abs/1910.09695
Publikováno v:
Journal of Statistical Planning and Inference (2020) 207, 10-26
We consider the confidence interval centered on a frequentist model averaged estimator that was proposed by Buckland, Burnham & Augustin (1997). In the context of a simple testbed situation involving two linear regression models, we derive exact expr
Externí odkaz:
http://arxiv.org/abs/1906.07933
Autor:
Kabaila, Paul, Wijethunga, Christeen
Publikováno v:
Stat, 8, e233 (2019)
Bootstrap smoothed (bagged) estimators have been proposed as an improvement on estimators found after preliminary data-based model selection. Efron, 2014, derived a widely applicable formula for a delta method approximation to the standard deviation
Externí odkaz:
http://arxiv.org/abs/1903.06552
Autor:
Kabaila, Paul, Ranathunga, Nishika
Publikováno v:
Computational Statistics (2021) 36, 313-332
We consider the problem of numerically evaluating the expected value of a smooth bounded function of a chi-distributed random variable, divided by the square root of the number of degrees of freedom. This problem arises in the contexts of simultaneou
Externí odkaz:
http://arxiv.org/abs/1902.06861
Autor:
Leeb, Hannes, Kabaila, Paul
Publikováno v:
J. R. Stat. Soc. Ser. B Stat. Methodol., 79:801-813, 2017
In the Gaussian linear regression model (with unknown mean and variance), we show that the standard confidence set for one or two regression coefficients is admissible in the sense of Joshi (1969). This solves a long-standing open problem in mathemat
Externí odkaz:
http://arxiv.org/abs/1809.07541
Publikováno v:
Statistica Neerlandica (2021) 75, 4-23
Consider a linear regression model and suppose that our aim is to find a confidence interval for a specified linear combination of the regression parameters. In practice, it is common to perform a Durbin-Watson pretest of the null hypothesis of zero
Externí odkaz:
http://arxiv.org/abs/1804.04306