Alisa Kirichenko, Ya. Nikitin (2014)
Open Mathematics
We find precise small deviation asymptotics with respect to the Hilbert norm for some special Gaussian processes connected to two regression schemes studied by MacNeill and his coauthors. In addition, we also obtain precise small deviation asymptotics for the detrended Brownian motion and detrended Slepian process.
Štulajter, F. (1997)
Acta Mathematica Universitatis Comenianae. New Series
Tabatabai, M.A., Singh, K.P. (1996)
Southwest Journal of Pure and Applied Mathematics [electronic only]
Andrej Pázman (1984)
Kybernetika
Lubomír Kubáček (2007)
Mathematica Slovaca
Lubomír Kubáček, Eva Fišerová (2003)
Mathematica Slovaca
František Štulajter (1988)
Aplikace matematiky
The model of quadratic regression is studied by means of the projection pursuit method. This method leads to a decomposition of the matrix of quadratic regression, which can be used for an estimation of this matrix from the data observed.
Gejza Wimmer (1995)
Applications of Mathematics
The properly recorded standard deviation of the estimator and the properly recorded estimate are introduced. Bounds for the locally best linear unbiased estimator and estimate and also confidence regions for a linearly unbiasedly estimable linear functional of unknown parameters of the mean value are obtained in a special structure of nonlinear regression model. A sufficient condition for obtaining the properly recorded estimate in this model is also given.
Mirta Benšić (2015)
Discussiones Mathematicae Probability and Statistics
We introduce and analyze a class of estimators for distribution parameters based on the relationship between the distribution function and the empirical distribution function. This class includes the nonlinear least squares estimator and the weighted nonlinear least squares estimator which has been used in parameter estimation for lifetime data (see e.g. [6, 8]) as well as the generalized nonlinear least squares estimator proposed in [3]. Sufficient conditions for consistency and asymptotic normality...
Serge Degerine (1982)
Annales de l'I.H.P. Probabilités et statistiques
Theo K. Dijkstra (1995)
Metrika
Hu, Hongchang (2010)
Mathematical Problems in Engineering
Štefan Varga (1991)
Applications of Mathematics
In the paper four types of estimations of the linear function of the variance components are presented for the mixed linear model with expectation and covariance matrix .
Lubomír Kubáček (1996)
Mathematica Slovaca
Czesław Stępniak (1998)
Mathematica Slovaca
R. Palm, A. F. Iemma (1995)
Revue de Statistique Appliquée
A. Hanen (1980)
Mathématiques et Sciences Humaines
Marc Lavielle, Carenne Ludeña (2008)
ESAIM: Probability and Statistics
A method is introduced to select the significant or non null mean terms among a collection of independent random variables. As an application we consider the problem of recovering the significant coefficients in non ordered model selection. The method is based on a convenient random centering of the partial sums of the ordered observations. Based on L-statistics methods we show consistency of the proposed estimator. An extension to unknown parametric distributions is considered. Simulated examples...
G. S. Rogers (1983)
Applicationes Mathematicae
T.V. Ramanathan, M.B. Rajarshi
Metrika