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Estimation of second order parameters using probability weighted moments

Julien Worms, Rym Worms (2012)

ESAIM: Probability and Statistics

The P.O.T. method (Peaks Over Threshold) consists in using the generalized Pareto distribution (GPD) as an approximation for the distribution of excesses over a high threshold. In this work, we use a refinement of this approximation in order to estimate second order parameters of the model using the method of probability-weighted moments (PWM): in particular, this leads to the introduction of a new estimator for the second order parameter ρ, which will be compared to other recent estimators through...

Estimation of second order parameters using probability weighted moments

Julien Worms, Rym Worms (2012)

ESAIM: Probability and Statistics

The P.O.T. method (Peaks Over Threshold) consists in using the generalized Pareto distribution (GPD) as an approximation for the distribution of excesses over a high threshold. In this work, we use a refinement of this approximation in order to estimate second order parameters of the model using the method of probability-weighted moments (PWM): in particular, this leads to the introduction of a new estimator for the second order parameter ρ, which will be compared to other recent estimators through...

Estimation of summary characteristics from replicated spatial point processes

Zbyněk Pawlas (2011)

Kybernetika

Summary characteristics play an important role in the analysis of spatial point processes. We discuss various approaches to estimating summary characteristics from replicated observations of a stationary point process. The estimators are compared with respect to their integrated squared error. Simulations for three basic types of point processes help to indicate the best way of pooling the subwindow estimators. The most appropriate way depends on the particular summary characteristic, edge-correction...

Estimation of the spectral density of a homogeneous random stable discrete time field.

Nicolay N. Demesh, Sergey L. Chekhmenok (2005)

SORT

In earlier papers, 2π-periodic spectral data windows have been used in spectral estimation of discrete- time random fields having finite second-order moments. In this paper, we show that 2π-periodic spectral windows can also be used to construct estimates of the spectral density of a homogeneous symmetric α-stable discrete-time random field. These fields do not have second-order moments if 0 < α < 2. We construct an estimate of the spectrum, calculate the asymptotic mean and variance,...

Estimation of the spectral moment by means of the extrema.

Enrique M. Cabaña (1985)

Trabajos de Estadística e Investigación Operativa

An estimator of the standard deviation of the first derivative of a stationary Gaussian process with known variance and two continuous derivatives, based on the values of the relative maxima and minima, is proposed, and some of its properties are considered.

Estimation of the transition density of a Markov chain

Mathieu Sart (2014)

Annales de l'I.H.P. Probabilités et statistiques

We present two data-driven procedures to estimate the transition density of an homogeneous Markov chain. The first yields a piecewise constant estimator on a suitable random partition. By using an Hellinger-type loss, we establish non-asymptotic risk bounds for our estimator when the square root of the transition density belongs to possibly inhomogeneous Besov spaces with possibly small regularity index. Some simulations are also provided. The second procedure is of theoretical interest and leads...

Estimators of the asymptotic variance of stationary point processes - a comparison

Michaela Prokešová (2011)

Kybernetika

We investigate estimators of the asymptotic variance σ 2 of a d –dimensional stationary point process Ψ which can be observed in convex and compact sampling window W n = n W . Asymptotic variance of Ψ is defined by the asymptotic relation V a r ( Ψ ( W n ) ) ∼ σ 2 | W n | (as n → ∞ ) and its existence is guaranteed whenever the corresponding reduced covariance measure γ red ( 2 ) ( · ) has finite total variation. The three estimators discussed in the paper are the kernel estimator, the estimator based on the second order intesity of the point process and the...

Estudio bayesiano de los periodos de ocupación y desocupación en una cola M/M/1/∞/FIFO en equilibrio.

Carmen Armero Cervera (1986)

Trabajos de Investigación Operativa

En este artículo, para un modelo de colas M/M/1/∞/FIFO en equilibrio, se obtiene la distribución predictiva del tiempo de duración de un período de ocupación, y de desocupación de la cola, así como la distribución predictiva final del número de personas atendidas en un período de ocupación, y la probabilidad de que éste sea finito. Finalmente, dichos resultados se aplican en una línea de espera concreta.

Estudio del carácter markoviano fuerte y regularidades de la solución de ecuaciones integrales estocásticas Ito generalizadas.

Ramón Gutiérrez Jáimez, Josefa Linares Pérez (1985)

Trabajos de Estadística e Investigación Operativa

El objetivo de este trabajo es un estudio sobre los caracteres felleriano y markoviano fuerte y las propiedades de regularidad del proceso solución de una ecuación integral estocástica generalizada (tipo Ito), pero generalizada en el sentido de considerar una formulación en términos de procesos operador-valuados. Esta formulación generaliza simultánea e independientemente las integrales de Cabaña y Daletsky.

Estudio del proceso de salida en un modelo D/Er/1.

Belén Castro Iñigo (1992)

Trabajos de Investigación Operativa

En este artículo se derivan expresiones para la distribución y momentos de las variables tiempo hasta la n-ésima salida y tiempo entre salidas, en modelos de la forma D/Er/1. Se incluyen expresiones obtenidas a partir de los resultados anteriores para las distribuciones transitorias de los tiempos de salida en diferentes modelos tándem. Por último, como aplicación de los resultados se incluye un ejemplo útil para la toma de decisiones en un sistema sanitario.

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