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Renormalization group of and convergence to the LISDLG process

Endre Iglói (2010)

ESAIM: Probability and Statistics

The LISDLG process denoted by J(t) is defined in Iglói and Terdik [ESAIM: PS7 (2003) 23–86] by a functional limit theorem as the limit of ISDLG processes. This paper gives a more general limit representation of J(t). It is shown that process J(t) has its own renormalization group and that J(t) can be represented as the limit process of the renormalization operator flow applied to the elements of some set of stochastic processes. The latter set consists of IGSDLG processes which are generalizations...

Renormalization group of and convergence to the LISDLG process

Endre Iglói (2004)

ESAIM: Probability and Statistics

The LISDLG process denoted by J ( t ) is defined in Iglói and Terdik [ESAIM: PS 7 (2003) 23–86] by a functional limit theorem as the limit of ISDLG processes. This paper gives a more general limit representation of J ( t ) . It is shown that process J ( t ) has its own renormalization group and that J ( t ) can be represented as the limit process of the renormalization operator flow applied to the elements of some set of stochastic processes. The latter set consists of IGSDLG processes which are generalizations of the ISDLG...

Representación canónica simultánea de poblaciones y variables: una aplicación al estudio de enfermedades renales.

Martín Ríos, Angel Villarroya, Esteban Vegas, Josep M. Oller (1991)

Qüestiió

En este trabajo se describe una metodología que nos permite representar simultáneamente poblaciones estadísticas y variables aleatorias, así como transformaciones admisibles de las mismas. Para ello se representan las variables aleatorias, o sus transformadas, en el espacio tangente a la variedad de las poblaciones estadísticas, a continuación se proyectan en dicha variedad y, finalmente, se aplica un análisis canónico de poblaciones para su representación en un espacio de dimensión reducida. Los...

Representación de datos en meteorología mediante gráficos animados: episodios de lluvia.

Jorge-Luis Navarro (1987)

Qüestiió

Los campos escalares, bidimensionales y dependientes del tiempo, se representan generalmente en Meteorología mediante una sucesión de imágenes o análisis separados con una interdistancia temporal adecuada. Esta técnica alcanza su máximo desarrollo en lo que se conoce como gráfico animado.En el presente artículo se describen brevemente los procesos que, a partir de los datos, culminan con la generación de un análisis, imagen o fotograma, particularizando al caso de episodios de lluvia. Tras un resumen...

Restricted estimation in unbalanced factorial models: an APL programs package.

José M. Prieto, José M. Caridad (1988)

Qüestiió

This paper describes a set of programs that provide researchers with restricted effect estimations in unbalanced factorial models when several weighing systems are imposed upon those models. The main program performing such an analysis is known as REUFM, and is written in APL⊗PLUS for IBM/PC microcomputers. An example is given in order to ilustrate the programs.

Reversible jump MCMC for two-state multivariate Poisson mixtures

Jani Lahtinen, Jouko Lampinen (2003)

Kybernetika

The problem of identifying the source from observations from a Poisson process can be encountered in fault diagnostics systems based on event counters. The identification of the inner state of the system must be made based on observations of counters which entail only information on the total sum of some events from a dual process which has made a transition from an intact to a broken state at some unknown time. Here we demonstrate the general identifiability of this problem in presence of multiple...

Ridge estimation of covariance matrix from data in two classes

Yi Zhou, Bin Zhang (2024)

Applications of Mathematics

This paper deals with the problem of estimating a covariance matrix from the data in two classes: (1) good data with the covariance matrix of interest and (2) contamination coming from a Gaussian distribution with a different covariance matrix. The ridge penalty is introduced to address the problem of high-dimensional challenges in estimating the covariance matrix from the two-class data model. A ridge estimator of the covariance matrix has a uniform expression and keeps positive-definite, whether...

Ridge Estimator Revisited

Lubomír Kubáček (2012)

Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica

Bad conditioned matrix of normal equations in connection with small values of model parameters is a source of problems in parameter estimation. One solution gives the ridge estimator. Some modification of it is the aim of the paper. The behaviour of it in models with constraints is investigated as well.

Risk bounds for mixture density estimation

Alexander Rakhlin, Dmitry Panchenko, Sayan Mukherjee (2005)

ESAIM: Probability and Statistics

In this paper we focus on the problem of estimating a bounded density using a finite combination of densities from a given class. We consider the Maximum Likelihood Estimator (MLE) and the greedy procedure described by Li and Barron (1999) under the additional assumption of boundedness of densities. We prove an O ( 1 n ) bound on the estimation error which does not depend on the number of densities in the estimated combination. Under the boundedness assumption, this improves the bound of Li and Barron by...

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