Universidade da Coruña. UDCDspace
(405 recursos)
UDCDspace é o repositorio dixital da Universidade da Coruña, un sistema que proporciona de xeito estable e seguro a preservación de documentos dixitais produto da actividade científica e institucional da UDC, e facilita a súa accesibilidade en Internet.
Mostrando recursos 1 - 17 de 17
1.
Recursive local polynomial regression under dependence conditions - Vilar Fernández, Juan Manuel; Vilar Fernández, José Antonio
In the case of the random design nonparametric regression, one recursive local polynomial smoother is considered. Expressions for the bias and the variance matrix of the estimators of the regression function and its derivatives are obtained under dependence conditions (strongly mixing processes). The obtained Mean Squared Error is shown to be larger than those of the analogous nonrecursive regression estimators, although retaining the same convergence rate. The properties of strong consistency with convergence rates are established for the proposed estimators. Finally, in order to analyse the influence of both the sample size and the dependence in the behaviour of the...
2.
Local polynomial regression estimation with correlated errors - Francisco Fernández, Mario; Vilar Fernández, Juan Manuel
In this paper, we study the nonparametric estimation of the regression
function and its derivatives using weighted local polynomial fitting. Consider
the fixed regression model and suppose that the random observation error is
coming from a strictly stationary stochastic process. Expressions for the bias
and the variance array of the estimators of the regression function and its
derivatives are obtained and joint asymptotic normality is established. The
influence of the dependence of the data is observed in the expression of the
variance. We also propose a variable bandwidth selection procedure. A simulation
study and an analysis with real economic data illustrate the proposed
selection method.
3.
Local polynomial regression smoothers with AR-error structure - Vilar Fernández, Juan Manuel; Francisco Fernández, Mario
Consider the fixed regression model with random observation error that follows an
AR(1) correlation structure. In this paper, we study the nonparametric estimation
of the regression function and its derivatives using a modified version of estimators
obtained by weighted local polynomial fitting. The asymptotic properties of the proposed
estimators are studied; expressions for the bias and the variance/covariance
matrix of the estimators are obtained and the joint asymptotic normality is established.
In a simulation study, a better behavior of the Mean Integrated Squared
Error of the proposed regression estimator with respect to that of the classical local
polynomial estimator is observed when the correlation of the observations is...
4.
On the uniform strong consistency of local polynomial regression under dependence conditions - Francisco Fernández, Mario; Vilar Fernández, Juan Manuel; Vilar Fernández, José Antonio
In this paper, nonparametric estimators of the regression function, and its derivatives, obtained by means of weighted local polynomial fitting are studied. Consider the fixed regression model where the error random variables are coming from a stationary stochastic process satisfying a mixing condition. Uniform strong consistency, along with rates, are established for these estimators. Furthermore, when the errors follow an AR(1) correlation structure, strong consistency properties are also derived for a modiÞed version of the local polynomial estimators proposed by Vilar-Fernández and Francisco-Fernández in (1).
6.
Bancos y cajas de ahorros: modelización del margen de beneficio por regresión múltiple: análisis comparativo - Vasallo Rapela, Alejandro M.; Vilar Fernández, Juan Manuel
Este trabajo desarrolla un modelo teórico que relaciona el margen de beneficio de las entidades financieras con variables estratégicas clave relativas a su tamaño (cuotas de mercado de depósitos y de préstamos) y variables que hacen referencia próxima a los servicios ofrecidos (los gastos generales y las amortizaciones). Como la medida de resultados elegida, el margen de explotación sobre productos totales, no tiene en cuenta el coste de los fondos propios, se incorpora al modelo el coste de capital a través de las siguientes variables: Activo Total/Ingresos y Fondos Propios/Ingresos. Las diferencias en la actuación de bancos y cajas de...
7.
Bootstrap tests for nonparametric comparison of regression curves with dependent errors - Vilar Fernández, Juan Manuel; Vilar Fernández, José Antonio
In this paper, the problem of testing the equality of regression curves with dependent data is studied. Several methods based on nonparametric estimators of the regression function are described. In this setting, the distribution of the test statistic is frequently unknown or difficult to compute, so an approximate test based on the asymptotic distribution of the statistic can be considered. Nevertheless, the asymptotic properties of the methods proposed in this work have been obtained under independence of the observations, and just one of these methods was studied in a context of dependence as reported by Vilar-Fernández and González-Manteiga (Statistics 58(2):8199,...
8.
Nonparametric forecasting in time series: a comparative study - Vilar Fernández, Juan Manuel; Cao Abad, Ricardo
The problem of predicting a future value of a time series is considered in this
paper. If the series follows a stationary Markov process, this can be done
by nonparametric estimation of the autoregression function. Two forecasting
algorithms are introduced. They only differ in the nonparametric kernel-type
estimator used: the Nadaraya-Watson estimator and the local linear estimator.
There are three major issues in the implementation of these algorithms: selection
of the autoregressor variables; smoothing parameter selection and computing
prediction intervals. These have been tackled using recent techniques
borrowed from the nonparametric regression estimation literature under dependence.
The performance of these nonparametric algorithms has been studied
by applying them to a...
9.
Weighted Local Nonparametric Regression with Dependent Errors: Study of Real Private Residential Fixed Investment in the USA - FRANCISCO-FERNANDEZ, MARIO; VILAR-FERNANDEZ, JUAN M.
This paper presents an overview of the existing literature on the nonparametric local
polynomial (LPR) estimator of the regression function and its derivatives when the observations are
dependent. When the errors of the regression model are correlated and follow an ARMA process,
Vilar-Fernández and Francisco-Fernández (2002) proposed a modification of the LPR estimator,
called the generalized local polynomial (GLPR) estimator, based on, first, transforming the regression
model to get uncorrelated errors and then applying the LPR estimator to the new model. Some of
the most significant asymptotic properties of these two weighted local estimators, including some
guidelines on how to select the bandwidth parameter, are reviewed. Finally,...
10.
Asymptotic properties of Local Polynomial regression with missing data and correlated errors - Pérez-González, A.; Vilar-Fernández, J. M.; González-Manteiga, W.
The main objective of this work is the nonparametric estimation of
the regression function with correlated errors when observations are
missing in the response variable. Two nonparametric estimators of
the regression function are proposed. The asymptotic properties of
these estimators are studied; expresions for the bias and the variance
are obtained and the joint asymptotic normality is established. A
simulation study is also included.
11.
Queues in Reliability - Ausín, M. Concepción
Queueing models can be useful in solving many complex reliability problems. Component
failures are usually interpreted as the arrival of customers and the repair or
replacement of failed components is typically associated with the service facility. A
distinctive characteristic of queues in reliability is that requests for service are usually
generated by a finite customer population because, in general, there are a limited number
of units, e.g. machines which can fail, and when they are all in the system, being
repaired or waiting for repair, no more can arrive. Thus the arrivals do not form a
renewal process as they may depend on the number of units...
12.
An introduction to quadrature and other numerical integration techniques - Ausín, M. Concepción
The objective in numerical integration is the approximation of a definite integral
using numerical techniques. There are a large number of numerical integration methods
in the literature and this article overviews some of the most common ones, namely, the
Newton-Cotes formulas, including the trapezoidal and Simpson's rules, and the Gaus-
sian quadrature. Difeerent procedures are compared and illustrated with examples.
Discussions about more advanced numerical integration procedures are also included.
13.
Bayesian estimation of the Gaussian mixture GARCH model - Ausín, M. Concepción; Galeano, Pedro
Bayesian inference and prediction for a generalized autoregressive conditional heteroskedastic (GARCH) model where the
innovations are assumed to follow a mixture of two Gaussian distributions is performed. The mixture GARCH model can capture
the patterns usually exhibited by many financial time series such as volatility clustering, large kurtosis and extreme observations.
A GriddyGibbs sampler implementation is proposed for parameter estimation and volatility prediction. Bayesian prediction of the
Value at Risk is also addressed providing point estimates and predictive intervals. The method is illustrated using the Swiss Market
Index.
14.
Bayesian control of the number of servers in a GI/M/c queueing system - Ausín, M. Concepción; Lillo, Rosa E.; Wiper, Michael P.
In this paper we consider the problem of designing a GI/M/c queueing system. Given arrival and service data, our objective
is to choose the optimal number of servers so as to minimize an expected cost function which depends on quantities, such as the
number of customers in the queue. A semiparametric approach based on Erlang mixture distributions is used to model the general
interarrival time distribution. Given the sample data, Bayesian Markov Chain Monte Carlo methods are used to estimate the system
parameters and the predictive distributions of the usual performance measures. We can then use these estimates to minimize the
steady-state expected total cost...
15.
Bayesian estimation for the M/G/1 queue using a phase-type approximation - Ausín, M. Concepción; Wiper, Michael P.; Lillo, Rosa E.
This article deals with Bayesian inference and prediction for M/G/1 queueing systems. The
general service time density is approximated with a class of Erlang mixtures which are phase-type
distributions. Given this phase-type approximation, an explicit evaluation of measures such as
the stationary queue size, waiting time and busy period distributions can be obtained. Given
arrival and service data, a Bayesian procedure based on reversible jump Markov Chain Monte
Carlo methods is proposed to estimate system parameters and predictive distributions.
16.
Bayesian estimation of ruin probabilities with heterogeneous and heavy-tailed insurance claim size distribution - Ausín, M. Concepción; Lopes, Hedibert F.
This paper describes a Bayesian approach to make inference for risk reserve processes with unknown claim size distribution. A flexible model based on mixtures of Erlang distributions is proposed to approximate the special features frequently observed in insurance claim sizes such as long tails and heterogeneity. A Bayesian density estimation approach for the claim sizes is implemented using reversible jump Markov Chain Monte Carlo methods. An advantage of the considered mixture model is that it belongs to the
class of phase-type distributions and then, explicit evaluations of the ruin probabilities are possible. Furthermore, from a statistical point of view, the parametric...
17.
Bayesian prediction of the transient behaviour and busy period in short and long-tailed GI/G/1 queueing systems - Ausín, M. Concepción; Wiper, Michael P.; Lillo, Rosa E.
Bayesian inference for the transient behavior and duration of a busy period in a single server queueing
system with general, unknown distributions for the interarrival and service times is investigated. Both
the interarrival and service time distributions are approximated using the dense family of Coxian distributions. A suitable reparameterization allows the definition of a non-informative prior and Bayesian
inference is then undertaken using reversible jump Markov chain Monte Carlo methods. An advantage of
the proposed procedure is that heavy tailed interarrival and service time distributions such as the Pareto
can be well approximated. The proposed procedure for estimating the system measures is based on
recent theoretical...
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