An extension of Billingsley’s uniform boundedness theorem to higher-dimensional $M$-processes

Jana Jurečková; Pranab Kumar Sen

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Displaying similar documents to “An extension of Billingsley’s uniform boundedness theorem to higher-dimensional $M$ -processes”

Regression quantiles and trimmed least squares estimator under a general design

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A counting process model of survival of parallel load-sharing system

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A system composed from a set of independent and identical parallel units is considered and its resistance (survival) against an increasing load is modelled by a counting process model, in the framework of statistical survival analysis. The objective is to estimate the (nonparametrized) hazard function of the distribution of loads breaking the units of the system (i. e. their breaking strengths), to derive the large sample properties of the estimator, and to propose a goodness-of-fit...

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On cumulative process model and its statistical analysis

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The notion of the counting process is recalled and the idea of the ‘cumulative’ process is presented. While the counting process describes the sequence of events, by the cumulative process we understand a stochastic process which cumulates random increments at random moments. It is described by an intensity of the random (counting) process of these moments and by a distribution of increments. We derive the martingale – compensator decomposition of the process and then we study the estimator...

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

František Štulajter (1991)

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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.

Displaying similar documents to “An extension of Billingsley’s uniform boundedness theorem to higher-dimensional M -processes”

Regression quantiles and trimmed least squares estimator under a general design

A counting process model of survival of parallel load-sharing system

Robust time series analysis: a survey

On cumulative process model and its statistical analysis

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

Displaying similar documents to “An extension of Billingsley’s uniform boundedness theorem to higher-dimensional $M$ -processes”