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

Displaying 1 – 20 of 20

Showing per page

Change point detection in vector autoregression

Zuzana Prášková (2018)

Kybernetika

In the paper a sequential monitoring scheme is proposed to detect instability of parameters in a multivariate autoregressive process. The proposed monitoring procedure is based on the quasi-likelihood scores and the quasi-maximum likelihood estimators of the respective parameters computed from a training sample, and it is designed so that the sequential test has a small probability of a false alarm and asymptotic power one as the size of the training sample is sufficiently large. The asymptotic...

Combining forecasts using the least trimmed squares

Jan Ámos Víšek (2001)

Kybernetika

Employing recently derived asymptotic representation of the least trimmed squares estimator, the combinations of the forecasts with constraints are studied. Under assumption of unbiasedness of individual forecasts it is shown that the combination without intercept and with constraint imposed on the estimate of regression coefficients that they sum to one, is better than others. A numerical example is included to support theoretical conclusions.

Comportamiento de los contrastes ADF, PP y KPSS al trabajar con series ajustadas de estacionalidad.

Tomás del Barrio Castro, Ana del Sur Mora, Jordi Suriñach Caralt (2001)

Qüestiió

En este trabajo se analiza el comportamiento de los tests de raíces unitarias cuando se utilizan los componentes ciclo-tendencia obtenidos a partir de procedimientos de extracción de señales en lugar de utilizar las series originales. Adicionalmente se intenta detectar las causas finales de los efectos perniciosos observados. Los procedimientos de extracción de señales analizados son el basado en modelos ARIMA y el filtro de líneas aéreas modificado. Un ejercicio de simulación nos permite concluir...

Computational aspects of robust Holt-Winters smoothing based on M -estimation

Christophe Croux, Sarah Gelper, Roland Fried (2008)

Applications of Mathematics

To obtain a robust version of exponential and Holt-Winters smoothing the idea of M -estimation can be used. The difficulty is the formulation of an easy-to-use recursive formula for its computation. A first attempt was made by Cipra (Robust exponential smoothing, J. Forecast. 11 (1992), 57–69). The recursive formulation presented there, however, is unstable. In this paper, a new recursive computing scheme is proposed. A simulation study illustrates that the new recursions result in smaller forecast...

Computational intensive methods for prediction and imputation in time series analysis

Maria Manuela Neves, Clara Cordeiro (2011)

Discussiones Mathematicae Probability and Statistics

One of the main goals in times series analysis is to forecast future values. Many forecasting methods have been developed and the most successful are based on the concept of exponential smoothing, based on the principle of obtaining forecasts as weighted combinations of past observations. Classical procedures to obtain forecast intervals assume a known distribution for the error process, what is not true in many situations. A bootstrap methodology can be used to compute distribution free forecast...

Concatenación temporal de modelos espaciales y su aplicación al estudio de la meningitis en España.

Juan Ferrándiz Ferragud, Ferrán Martínez Navarro, Pilar Sanmartín Fita (2001)

Qüestiió

La cartografía de enfermedades infecciosas en periodos sucesivos plantea la necesidad de su extensión al caso dinámico. En este trabajo proponemos la concatenación temporal de modelos auto-regresivos espaciales para abordar el análisis de mortalidad por meningitis en España en el período 1950-1990 con datos agregados a nivel provincial. Para la estimación v selección del modelo usamos técnicas basadas en la función de verosimilitud.

Consistency of linear and quadratic least squares estimators in regression models with covariance stationary errors

František Štulajter (1991)

Applications of Mathematics

The least squres invariant quadratic estimator of an unknown covariance function of a stochastic process is defined and a sufficient condition for consistency of this estimator is derived. The mean value of the observed process is assumed to fulfil a linear regresion model. A sufficient condition for consistency of the least squares estimator of the regression parameters is derived, too.

Convergence model of interest rates of CKLS type

Zuzana Zíková, Beáta Stehlíková (2012)

Kybernetika

This paper deals with convergence model of interest rates, which explains the evolution of interest rate in connection with the adoption of Euro currency. Its dynamics is described by two stochastic differential equations – the domestic and the European short rate. Bond prices are then solutions to partial differential equations. For the special case with constant volatilities closed form solutions for bond prices are known. Substituting its constant volatilities by instantaneous volatilities we...

Copula approach to residuals of regime-switching models

Anna Petričková, Magda Komorníková (2012)

Kybernetika

The autocorrelation function describing the linear dependence is not suitable for description of residual dependence of the regime-switching models. In this contribution, inspired by Rakonczai ([20]), we will model the residual dependence of the regime-switching models (SETAR, LSTAR and ESTAR) with the autocopulas (Archimedean, EV and their convex combinations) and construct improved quality models for the original real time series.

Covariance structure of wide-sense Markov processes of order k ≥ 1

Arkadiusz Kasprzyk, Władysław Szczotka (2006)

Applicationes Mathematicae

A notion of a wide-sense Markov process X t of order k ≥ 1, X t ∼ W M ( k ) , is introduced as a direct generalization of Doob’s notion of wide-sense Markov process (of order k=1 in our terminology). A base for investigation of the covariance structure of X t is the k-dimensional process x t = ( X t - k + 1 , . . . , X t ) . The covariance structure of X t ∼ W M ( k ) is considered in the general case and in the periodic case. In the general case it is shown that X t ∼ W M ( k ) iff x t is a k-dimensional WM(1) process and iff the covariance function of x t has the triangular property....

Criteria for optimal design of small-sample experiments with correlated observations

Andrej Pázman (2007)

Kybernetika

We consider observations of a random process (or a random field), which is modeled by a nonlinear regression with a parametrized mean (or trend) and a parametrized covariance function. Optimality criteria for parameter estimation are to be based here on the mean square errors (MSE) of estimators. We mention briefly expressions obtained for very small samples via probability densities of estimators. Then we show that an approximation of MSE via Fisher information matrix is possible, even for small...

Currently displaying 1 – 20 of 20

Page 1