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Se estudian modificaciones de las técnicas de validación cruzada de Kullback-Leibler y mínimos cuadrados para obtener el parámetro de suavización asociado a un estimador general no paramétrico de la función de densidad, a partir de la muestra, en el supuesto de que los datos verifican alguna condición débil de dependencia.Se demuestra que los parámetros obtenidos por estas dos técnicas son asintóticamente óptimos. Y se realiza un estudio de simulación.
Se introduce el concepto general de medida de inquietud (o medida de incertidumbre cualitativo-cuantitativa) sobre una clase de esquemas dobles de probabilidades y utilidades; y se estudian algunas de sus propiedades: invariancia, componibilidad, etc. Finaliza el trabajo con la caracterización de una clase particular de medidas.
El propósito de este artículo es revisar, relacionar e interpretar tests de hipótesis, tipo score, para contrastar la especificación de modelos de series temporales múltiples, así como obtener unos resultados sobre los estadísticos asociados, lo más simples posibles, a fin de utilizarlos en la etapa de identificación de los modelos.
Proof of a result generalizing a Hoeffding's paper abount independence.
A sub-exponential Weibull random variable may be expressed as a quotient of a unit exponential to an independent strictly positive stable random variable. Based on this property, we propose a test for exponentiality which is consistent against Weibull and Gamma distributions with shape parameter less than unity. A comparison with other procedures is also included.
2000 Mathematics Subject Classification: 62H15, 62H12.We consider variables with joint multivariate normal distribution and suppose that the sample correlation matrix has missing elements, located in one and the same column. Under these assumptions we derive the maximum likelihood ratio test for independence of the variables. We obtain also the maximum likelihood estimations for the missing values.
In regular multivariate regression model a test of linear hypothesis is dependent on a structure and a knowledge of the covariance matrix. Several tests procedures are given for the cases that the covariance matrix is either totally unknown, or partially unknown (variance components), or totally known.
The paper concentrates on modeling the data that can be described by a homogeneous or non-homogeneous Poisson process. The goal is to decide whether the intensity of the process is constant or not. In technical practice, e.g., it means to decide whether the reliability of the system remains the same or if it is improving or deteriorating. We assume two situations. First, when only the counts of events are known and, second, when the times between the events are available. Several statistical tests...
This paper considers the problem of testing a sub-hypothesis in homoscedastic linear regression models when the covariate and error processes form independent long memory moving averages. The asymptotic null distribution of the likelihood ratio type test based on Whittle quadratic forms is shown to be a chi-square distribution. Additionally, the estimators of the slope parameters obtained by minimizing the Whittle dispersion is seen to be -consistent for all values of the long memory parameters...
In the paper a test of the hypothesis , on parameters of the normal distribution is presented, and explicit formulas for critical regions are derived for finite sample sizes. Asymptotic null distribution of the test statistic is investigated under the assumption, that the true distribution possesses the fourth moment.
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