All a b c d e f g h i j k l m n o p q r s t u v w x y z Other

Page 1 Next

Displaying 1 – 20 of 659

Showing per page

3-dimensional multivertex reconstruction from 2-dimensional tracks observations using likelihood inference

Nikolai I. Chernov, Genadij A. Ososkov, Luc Pronzato (1992)

Applications of Mathematics

Let v 1 , v 2 , . . . , v k be vertices in the X Y Z -space, each vertex producing several tracks (straight lines) emanating from it within a narrow cone with a small angle about a fixed direction ( Z -axis). Each track is detected (by drift chambers or other detectors) by its projections on X Y and Y Z views independently with small errors. An automated method is suggested for the reconstruction of vertices from noisy observations of the tracks projections. The procedure is based on the likelihood inference for mixtures. An illustrative...

A Bayesian estimate of the risk of tick-borne diseases

Marek Jiruše, Josef Machek, Viktor Beneš, Petr Zeman (2004)

Applications of Mathematics

The paper considers the problem of estimating the risk of a tick-borne disease in a given region. A large set of epidemiological data is evaluated, including the point pattern of collected cases, the population map and covariates, i.e. explanatory variables of geographical nature, obtained from GIS. The methodology covers the choice of those covariates which influence the risk of infection most. Generalized linear models are used and AIC criterion yields the decision. Further, an empirical Bayesian...

A comparative study of small area estimators.

Laureano Santamaría, Domingo Morales, Isabel Molina (2004)

SORT

It is known that direct-survey estimators of small area parameters, calculated with the data from the given small area, often present large mean squared errors because of small sample sizes in the small areas. Model-based estimators borrow strength from other related areas to avoid this problem. How small should domain sample sizes be to recommend the use of model-based estimators? How robust are small area estimators with respect to the rate sample size/number of domains?To give answers or recommendations...

A comparison of cointegration tests

Petr Mariel (1996)

Applications of Mathematics

In this paper some of the cointegration tests applied to a single equation are compared. Many of the existent cointegration tests are simply extensions of the unit root tests applied to the residuals of the cointegrating regression and the habitual H 0 is no cointegration. However, some non residual-based tests and some tests of the opposite null hypothesis have recently appeared in literature. Monte Carlo simulations have been used for the power comparison of the nine selected tests ( A D F , Z ^ α , Z ^ t , D H S ,...

A comparison of linearization and quadratization domains

Anna Jenčová (1997)

Applications of Mathematics

In a nonlinear model, the linearization and quadratization domains are considered. In the case of a locally quadratic model, explicit expressions for these domains are given and the domains are compared.

A Gram-Schmidt orthogonalizing process of design matrices in linear models as an estimating procedure of covariance components.

Gabriela Beganu (2005)

RACSAM

Se considera un modelo lineal mixto multivariante equilibrado sin interacción para el que las matrices de las formas cuadráticas necesarias para estimar la covarianza de las componentes se expresan mediante operadores lineales en espacios con producto interior de dimensión finita. El propósito de este artículo es demostrar que las formas cuadráticas obtenidas por el proceso de ortogonalización de Gram-Schmidt de las matrices de diseño son combinaciones lineales de las formas cuadráticas derivadas...

A model and application of binary random sequence with probabilities depending on history

Petr Volf, Tomáš Kouřim (2024)

Kybernetika

This paper presents a model of binary random sequence with probabilities depending on previous sequence values as well as on a set of covariates. Both these dependencies are expressed via the logistic regression model, such a choice enables an easy and reliable model parameters estimation. Further, a model with time-depending parameters is considered and method of solution proposed. The main objective is then the application dealing with both artificial and real data cases, illustrating the method...

A modification of the Hartung-Knapp confidence interval on the variance component in two-variance-component models

Barbora Arendacká (2007)

Kybernetika

We consider a construction of approximate confidence intervals on the variance component σ 1 2 in mixed linear models with two variance components with non-zero degrees of freedom for error. An approximate interval that seems to perform well in such a case, except that it is rather conservative for large σ 1 2 / σ 2 , was considered by Hartung and Knapp in [hk]. The expression for its asymptotic coverage when σ 1 2 / σ 2 → ∞ suggests a modification of this interval that preserves some nice properties of the original and that...

A new stochastic restricted biased estimator under heteroscedastic or correlated error

Mustafa Ismaeel Alheety (2011)

ESAIM: Probability and Statistics

In this paper, under the linear regression model with heteroscedastic and/or correlated errors when the stochastic linear restrictions on the parameter vector are assumed to be held, a generalization of the ordinary mixed estimator (GOME), ordinary ridge regression estimator (GORR) and Generalized least squares estimator (GLSE) is proposed. The performance of this new estimator against GOME, GORR, GLS and the stochastic restricted Liu estimator (SRLE) [Yang and Xu, Statist. Papers 50 (2007) 639–647]...

Currently displaying 1 – 20 of 659

Page 1 Next