Página 1 dos resultados de 2968 itens digitais encontrados em 0.017 segundos

Maximum likelihood estimation with nonlinear regression in polarographic and potentiometric studies

Pereira, J. L. G. C.; Pais, A. A. C. C.; Redinha, J. S.
Fonte: Universidade de Coimbra Publicador: Universidade de Coimbra
Tipo: Artigo de Revista Científica Formato: aplication/PDF
ENG
Relevância na Pesquisa
76.09%
In this work we review some aspects of maximum likelihood nonlinear modeling in polarographic and potentiometric techniques. Different algorithms, namely the Levenberg-Marquardt and the "error-in-variables" methods in parametric and Monte-Carlo nonparametric estimation are used. Conclusions are drawn upon the influence of experimental errors and error correlation, introduced via statistical weighting, in the accuracy and precision of the estimated parameters. Several of the tested alternatives, including regression on the signal variable alone with a global error weighting function, are shown to provide adequate representation of the experimental data.; http://www.sciencedirect.com/science/article/B6TF4-42MN77N-G/1/41f1ab649732a741006ed3b32e9ea5d8

Improved maximum-likelihood estimation in a regression model with general parametrization

LEMONTE, Artur J.
Fonte: TAYLOR & FRANCIS LTD Publicador: TAYLOR & FRANCIS LTD
Tipo: Artigo de Revista Científica
ENG
Relevância na Pesquisa
86.09%
We analyse the finite-sample behaviour of two second-order bias-corrected alternatives to the maximum-likelihood estimator of the parameters in a multivariate normal regression model with general parametrization proposed by Patriota and Lemonte [A. G. Patriota and A. J. Lemonte, Bias correction in a multivariate regression model with genereal parameterization, Stat. Prob. Lett. 79 (2009), pp. 1655-1662]. The two finite-sample corrections we consider are the conventional second-order bias-corrected estimator and the bootstrap bias correction. We present the numerical results comparing the performance of these estimators. Our results reveal that analytical bias correction outperforms numerical bias corrections obtained from bootstrapping schemes.; Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP); FAPESP (Brazil)

Parametric tail copula estimation and model testing

Haan, Laurens de; Neves, Cláudia; Peng, Liang
Fonte: Elsevier Publicador: Elsevier
Tipo: Artigo de Revista Científica
ENG
Relevância na Pesquisa
76.04%
Parametric models for tail copulas are being used for modeling tail dependence and maximum likelihood estimation is employed to estimate unknown parameters. However, two important questions seem unanswered in the literature: (1) What is the asymptotic distribution of the MLE and (2) how does one test the parametric model? In this paper, we answer these two questions in the case of a single parameter for ease of illustration. A simulation study is provided to investigate the finite sample performance of the proposed estimator and test.; FCT-POCI/MAT/58876/2004

Revisiting optimization algorithms for maximum likelihood estimation

Mai, Anh Tien
Fonte: Université de Montréal Publicador: Université de Montréal
Tipo: Thèse ou Mémoire numérique / Electronic Thesis or Dissertation
EN
Relevância na Pesquisa
86.32%
Parmi les méthodes d’estimation de paramètres de loi de probabilité en statistique, le maximum de vraisemblance est une des techniques les plus populaires, comme, sous des conditions l´egères, les estimateurs ainsi produits sont consistants et asymptotiquement efficaces. Les problèmes de maximum de vraisemblance peuvent être traités comme des problèmes de programmation non linéaires, éventuellement non convexe, pour lesquels deux grandes classes de méthodes de résolution sont les techniques de région de confiance et les méthodes de recherche linéaire. En outre, il est possible d’exploiter la structure de ces problèmes pour tenter d’accélerer la convergence de ces méthodes, sous certaines hypothèses. Dans ce travail, nous revisitons certaines approches classiques ou récemment d´eveloppées en optimisation non linéaire, dans le contexte particulier de l’estimation de maximum de vraisemblance. Nous développons également de nouveaux algorithmes pour résoudre ce problème, reconsidérant différentes techniques d’approximation de hessiens, et proposons de nouvelles méthodes de calcul de pas, en particulier dans le cadre des algorithmes de recherche linéaire. Il s’agit notamment d’algorithmes nous permettant de changer d’approximation de hessien et d’adapter la longueur du pas dans une direction de recherche fixée. Finalement...

A conditional likelihood approach to residual maximum likelihood estimation in generalized linear models

Smyth, G.; Verbyla, A.
Fonte: Wiley Publicador: Wiley
Tipo: Artigo de Revista Científica
Publicado em //1996 EN
Relevância na Pesquisa
86.31%
Residual maximum likelihood (REML) estimation is often preferred to maximum likelihood estimation as a method of estimating covariance parameters in linear models because it takes account of the loss of degrees of freedom in estimating the mean and produces unbiased estimating equations for the variance parameters. In this paper it is shown that REML has an exact conditional likelihood interpretation, where the conditioning is on an appropriate sufficient statistic to remove dependence on the nuisance parameters. This interpretation clarifies the motivation for REML and generalizes directly to non-normal models in which there is a low dimensional sufficient statistic for the fitted values. The conditional likelihood is shown to be well defined and to satisfy the properties of a likelihood function, even though this is not generally true when conditioning on statistics which depend on parameters of interest. Using the conditional likelihood representation, the concept of REML is extended to generalized linear models with varying dispersion and canonical link. Explicit calculation of the conditional likelihood is given for the one-way lay-out. A saddlepoint approximation for the conditional likelihood is also derived.; Gordon K. Smyth and Arunas P. Verbyla

Maximum likelihood estimation of circle parameters via convolution

Zelniker, Emanuel Emil; Clarkson, Vaughan L.
Fonte: IEEE: Institute of Electrical and Electronics Engineers Publicador: IEEE: Institute of Electrical and Electronics Engineers
Tipo: Artigo de Revista Científica
Publicado em //2006 EN
Relevância na Pesquisa
86.14%
The accurate fitting of a circle to noisy measurements of circumferential points is a much studied problem in the literature. In this paper, we present an interpretation of the maximum-likelihood estimator (MLE) and the Delogne–Kåsa estimator (DKE) for circle-center and radius estimation in terms of convolution on an image which is ideal in a certain sense. We use our convolution-based MLE approach to find good estimates for the parameters of a circle in digital images. In digital images, it is then possible to treat these estimates as preliminary estimates into various other numerical techniques which further refine them to achieve subpixel accuracy. We also investigate the relationship between the convolution of an ideal image with a “phase-coded kernel” (PCK) and the MLE. This is related to the “phase-coded annulus” which was introduced by Atherton and Kerbyson who proposed it as one of a number of new convolution kernels for estimating circle center and radius. We show that the PCK is an approximate MLE (AMLE). We compare our AMLE method to the MLE and the DKE as well as the Cramér–Rao Lower Bound in ideal images and in both real and synthetic digital images.; Emanuel E. Zelniker, Student Member, IEEE, and I. Vaughan L. Clarkson; Copyright © 2006 IEEE

Parameter identification of fluid line networks by frequency-domain maximum likelihood estimation

Zecchin, A.; White, L.; Lambert, M.; Simpson, A.
Fonte: Academic Press Ltd Elsevier Science Publicador: Academic Press Ltd Elsevier Science
Tipo: Artigo de Revista Científica
Publicado em //2013 EN
Relevância na Pesquisa
96.14%
The accurate hydraulic simulation of fluid line networks is important for many applications, however, in many instances (such as surge analysis in water distribution networks) the system parameters are subject to much uncertainty. This paper presents a parameter identification method for fluid line networks based on transient-state measurements of the hydraulic variables of pressure and ow within the network. From a Laplace-domain admittance matrix representation of the system, a measurement model is derived that decouples the influence of unmeasured state variables from the measured state variables. This de-coupled measurement model is used as the basis of the development of a frequency-domain maximum likelihood estimation method. The proposed method is applied to different case studies with successful results.; Aaron C. Zecchin, Langford B. White, Martin F. Lambert, Angus R. Simpson

How to fit models of recognition memory data using maximum likelihood

Dunn, J.C.
Fonte: University of San Buenaventura Publicador: University of San Buenaventura
Tipo: Artigo de Revista Científica
Publicado em //2010 EN; ES
Relevância na Pesquisa
86.2%
The aim of this paper is to provide an introductory tutorial to how to fit different models of recognition memory using maximum likelihood estimation. It is in four main parts. The first part describes how recognition memory data is collected and analysed. The second part introduces four current models that will be fitted to the data. The third part describes in detail how a model is fit using maximum likelihood estimation. The fourth part examines how the fit of a model can be evaluated and the appropriate statistical test applied. = El propósito de este artículo es proveer un tutorial sobre cómo ajustar diferentes modelos de la memoria de reconocimiento usando estimación de máxima verosimilitud. El artículo presenta cuatro partes. Primero se describe cómo se analizan y obtienen datos en experimentos sobre la memoria de reconocimiento. En segundo lugar se presentan cuatro modelos recientes que serán ajustados a los datos. La tercera parte describe en detalle cómo se ajusta un modelo usando el procedimiento de estimación de máxima verosimilitud. Por último se examina cómo el modelo ajustado pueden ser evaluado y qué pruebas estadísticas pueden aplicarse para ello.; John C. Dunn; Spanish title: Cómo ajustar modelos de datos en experimentos sobre la memoria de reconcomiendo usando métodos de máxima verosimilitud Abstract and Keywords also in Spanish

Quasi-Maximum Likelihood estimation of Stochastic Volatility models

Ruiz, Esther
Fonte: Elsevier Publicador: Elsevier
Tipo: Artigo de Revista Científica Formato: application/pdf
Publicado em //1994 ENG
Relevância na Pesquisa
76%
Changes in variance or volatility over time can be modelled using stochastic volatility (SV) models. This approach is based on treating the volatility as an unobserved vatiable, the logarithm of which is modelled as a linear stochastic process, usually an autoregression. This article analyses the asymptotic and finite sample properties of a Quasi-Maximum Likelihood (QML) estimator based on the Kalman filter. The relative efficiency of the QML estimator when compared with estimators based on the Generalized Method of Moments is shown to be quite high for parameter values often found in empirical applications. The QML estimator can still be employed when the SV model is generalized to allow for distributions with heavier tails than the normal. SV models are finally fitted to daily observations on the yen/dollar exchange rate.; Publicado además en: Recent developments in Time Series, 2003, vol. 2, ISBN13: 9781840649512, pp. 117-134

A comparison of maximum likelihood models for fatigue strength characterization in materials exhibiting a fatigue limit

Pollak, Randall D.; Palazotto, Anthony N.
Fonte: Escola de Pós-Graduação Naval Publicador: Escola de Pós-Graduação Naval
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
86.09%
The article of record as published may be located at http://dx.doi.org/10.1016/j.probengmech.2008.06.006; In this study, various probabilistic models were considered to support fatigue strength design guidance in the ultra high-cycle regime (beyond 108 cycles), with particular application to Ti-6Al-4V, a titanium alloy common to aerospace applications. The random fatigue limit model of Pascual and Meeker and two proposed simplified models (bilinear and hyperbolic) used maximum likelihood estimation techniques to fit probabilistic stress-life curves to experimental data. The bilinear and hyperbolic models provided a good fit to large-sample experimental data for dual-phase Ti-6Al-4V and were then applied to a small- sample data set for a beta annealed variant of this alloy, providing an initial probabilistic estimate of beta annealed Ti-6Al-4V fatigue strength in the gigacycle regime. The bilinear and hyperbolic models are recommended for use in estimating probabilistic fatigue strength parameters in support of very high- cycle design criteria for metals with clearly defined fatigue limits and fairly constant scatter in fatigue strength.; This research was supported in part by the Air Force Research Laboratory's Materials and Manufacturing Directorate...

Estimação de maxima verossimilhança para processo de nascimento puro espaço-temporal com dados parcialmente com dados parcialmente observados; Maximum likelihood estimation for space-time pu birth process with missing data

Daniela Bento Fonsechi Goto
Fonte: Biblioteca Digital da Unicamp Publicador: Biblioteca Digital da Unicamp
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 10/09/2008 PT
Relevância na Pesquisa
96.25%
O objetivo desta dissertação é estudar estimação de máxima verossimilhança para processos de nascimento puro espacial para dois diferentes tipos de amostragem: a) quando há observação permanente em um intervalo [0, T]; b) quando o processo é observado após um tempo T fixo. No caso b) não se conhece o tempo de nascimento dos pontos, somente sua localização (dados faltantes). A função de verossimilhança pode ser escrita para o processo de nascimento puro não homogêneo em um conjunto compacto através do método da projeção descrito por Garcia and Kurtz (2008), como projeção da função de verossimilhança. A verossimilhança projetada pode ser interpretada como uma esperança e métodos de Monte Carlo podem ser utilizados para estimar os parâmetros. Resultados sobre convergência quase-certa e em distribuição são obtidos para a aproximação do estimador de máxima verossimilhança. Estudos de simulação mostram que as aproximações são adequadas; The goal of this work is to study the maximum likelihood estimation of a spatial pure birth process under two different sampling schemes: a) permanent observation in a fixed time interval [0, T]; b) observation of the process only after a fixed time T. Under scheme b) we don't know the birth times...

An information geometric approach to ML estimation with incomplete data: Application to semiblind MIMO channel identification

Zia, A.; Reilly, J.P.; Manton, Jonathan; shirani, S.
Fonte: Institute of Electrical and Electronics Engineers (IEEE Inc) Publicador: Institute of Electrical and Electronics Engineers (IEEE Inc)
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
76.17%
In this paper, we cast the stochastic maximum-likelihood estimation of parameters with incomplete data in an information geometric framework. In this vein, we develop the information geometric identification (IGID) algorithm. The algorithm consists of ite

Approximated Maximum Likelihood Estimation of Carrier Frequency Offset in Practical OFDM Systems

Ruan, Matt (Ming); Reed, Mark; Shi, Zhenning
Fonte: Institute of Electrical and Electronics Engineers (IEEE Inc) Publicador: Institute of Electrical and Electronics Engineers (IEEE Inc)
Tipo: Conference paper
Relevância na Pesquisa
76.15%
This paper proposes a high-performance and relatively low-complexity approximated maximum likelihood estimator (MLE) for carrier frequency offset (CFO) in practical orthogonal frequency multiplexing (OFDM) systems, where the preamble has repetition struct

Penalized maximum likelihood estimation and variable selection in geostatistics

Chu, Tingjin; Zhu, Jun; Wang, Haonan
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
66.3%
We consider the problem of selecting covariates in spatial linear models with Gaussian process errors. Penalized maximum likelihood estimation (PMLE) that enables simultaneous variable selection and parameter estimation is developed and, for ease of computation, PMLE is approximated by one-step sparse estimation (OSE). To further improve computational efficiency, particularly with large sample sizes, we propose penalized maximum covariance-tapered likelihood estimation (PMLE$_{\mathrm{T}}$) and its one-step sparse estimation (OSE$_{\mathrm{T}}$). General forms of penalty functions with an emphasis on smoothly clipped absolute deviation are used for penalized maximum likelihood. Theoretical properties of PMLE and OSE, as well as their approximations PMLE$_{\mathrm{T}}$ and OSE$_{\mathrm{T}}$ using covariance tapering, are derived, including consistency, sparsity, asymptotic normality and the oracle properties. For covariance tapering, a by-product of our theoretical results is consistency and asymptotic normality of maximum covariance-tapered likelihood estimates. Finite-sample properties of the proposed methods are demonstrated in a simulation study and, for illustration, the methods are applied to analyze two real data sets.; Comment: Published in at http://dx.doi.org/10.1214/11-AOS919 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)

Analyticity, Convergence and Convergence Rate of Recursive Maximum Likelihood Estimation in Hidden Markov Models

Tadić, Vladislav B.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
66.29%
This paper considers the asymptotic properties of the recursive maximum likelihood estimation in hidden Markov models. The paper is focused on the asymptotic behavior of the log-likelihood function and on the point-convergence and convergence rate of the recursive maximum likelihood estimator. Using the principle of analytical continuation, the analyticity of the asymptotic log-likelihood function is shown for analytically parameterized hidden Markov models. Relying on this fact and some results from differential geometry (Lojasiewicz inequality), the almost sure point-convergence of the recursive maximum likelihood algorithm is demonstrated, and relatively tight bounds on the convergence rate are derived. As opposed to the existing result on the asymptotic behavior of maximum likelihood estimation in hidden Markov models, the results of this paper are obtained without assuming that the log-likelihood function has an isolated maximum at which the Hessian is strictly negative definite.

Consistency of maximum likelihood estimation for some dynamical systems

McGoff, Kevin; Mukherjee, Sayan; Nobel, Andrew; Pillai, Natesh
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
66.29%
We consider the asymptotic consistency of maximum likelihood parameter estimation for dynamical systems observed with noise. Under suitable conditions on the dynamical systems and the observations, we show that maximum likelihood parameter estimation is consistent. Our proof involves ideas from both information theory and dynamical systems. Furthermore, we show how some well-studied properties of dynamical systems imply the general statistical properties related to maximum likelihood estimation. Finally, we exhibit classical families of dynamical systems for which maximum likelihood estimation is consistent. Examples include shifts of finite type with Gibbs measures and Axiom A attractors with SRB measures.; Comment: Published in at http://dx.doi.org/10.1214/14-AOS1259 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)

Blind Estimation of Residual Timing Error in OFDM Receivers: A Non-Data-Aided Maximum-Likelihood Approach

Athaudage, Chandranath R; Jayalath, Anagiyaddage Dhammik
Fonte: Institute of Electrical and Electronics Engineers (IEEE Inc) Publicador: Institute of Electrical and Electronics Engineers (IEEE Inc)
Tipo: Conference paper
Relevância na Pesquisa
76.19%
This paper proposes a novel non-data-aided maximum likelihood (ML) approach for the estimation of the residual timing error in OFDM receivers. The novel approach effectively utilizes the finite alphabet property of the received symbol constellation to perform a near perfect residual timing error estimation. Unlike some of the current techniques, the proposed approach requires no pilots and therefore is bandwidth efficient. Moreover, the reduced complexity version of the post-FFT ML algorithm minimizes the receiver computational burden. Simulation results show that the BER degradation due to residual timing error can be almost completely recovered for both AWGN and Rayleigh fading channel scenarios.

Adaptive MMSE Maximum Likelihood CDMA Multiuser Detection

Borah, D
Fonte: Institute of Electrical and Electronics Engineers (IEEE Inc) Publicador: Institute of Electrical and Electronics Engineers (IEEE Inc)
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
76.2%
The well known code division multiple access maximum likelihood receiver (MF-ML) uses a bank of matched filters as a generator of sufficient statistics for maximum likelihood detection of users' transmitted symbols. In this paper, the bank of matched filters is replaced by a bank of adaptive minimum mean squared error (MMSE) filters as the generator of sufficient statistics. This formal replacement of the MF bank by the adaptive MMSE filter bank has significant conceptual consequences and provides improvement by several performance measures. The adaptive MMSE-ML receiver's digital implementation is significantly computationally simplified. The advantages of the proposed adaptive MMSE-ML receiver over the MF-ML receiver are: 1) ability to perform joint synchronization, channel parameter estimation, and signal detection where the signal is sent over an unknown, slowly time-varying, frequency-selective multipath fading channel, 2) increased information capacity in a multicellular environment; and 3) significantly improved bit error rate (BER) performance in a multicellular mobile communications environment. The information capacity and the BER of the proposed MMSE-ML receiver are analyzed. Numerical results showing the BER performance of the MMSE-ML receiver in a multipath channel environment are presented.

Reduced complexity maximum likelihood sequence estimator for high-speed fiber optic communication systems

Carrer,H. S.; Crivelli,D. E.; Hueda,M. R.
Fonte: Latin American applied research Publicador: Latin American applied research
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/04/2005 EN
Relevância na Pesquisa
76%
In this paper we present a new reduced complexity maximum likelihood sequence detector for intensity modulation / direct detection (IM/DD) fiber optic systems. The proposed detector takes into account the presence of thermal and amplified spontaneous emission (ASE) noise. The results presented here show a negligible performance degradation from the optimum receiver, while implementation complexity is significantly reduced. The mathematical models derived in this paper are attractive for the design and analysis of very high speed optical receivers.

Maximum Likelihood Position Location with a Limited Number of References

Munoz-Rodriguez,D; Suarez-Robles,L; Vargas-Rosales,C; Rodriguez-Cruz,J. R.
Fonte: UNAM, Centro de Ciencias Aplicadas y Desarrollo Tecnológico Publicador: UNAM, Centro de Ciencias Aplicadas y Desarrollo Tecnológico
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/04/2011 EN
Relevância na Pesquisa
76.09%
A Position Location (PL) scheme for mobile users on the outskirts of coverage areas is presented. The proposed methodology makes it possible to obtain location information with only two land-fixed references. We introduce a general formulation and show that maximum-likelihood estimation can provide adequate PL information in this scenario. The Root Mean Square (RMS) error and error-distribution characterization are obtained for different propagation scenarios. In addition, simulation results and comparisons to another method are provided showing the accuracy and the robustness of the method proposed. We study accuracy limits of the proposed methodology for different propagation environments and show that even in the case of mismatch in the error variances, good PL estimation is feasible.