Pseudolikelihood equations for Potts MRF model parameter estimation on higher order neighborhood systems

This letter presents pseudolikelihood equations for the estimation of the Potts Markov random field model parameter on higher order neighborhood systems. The derived equation for second-order systems is a significantly reduced version of a recent result found in the literature (from 67 to 22 terms). Also, with the proposed method, a completely original equation for Potts model parameter estimation in third-order systems was obtained. These equations allow the modeling of less restrictive contextual systems for a large number of applications in a computationally feasible way. Experiments with both simulated and real remote sensing images provided good results.

Multiscale Analysis of Topographic Surface Roughness in the Midland Valley, Scotland

Surface roughness is an important geomorphological variable which has been used in the Earth and planetary sciences to infer material properties, current/past processes, and the time elapsed since formation. No single definition exists; however, within the context of geomorphometry, we use surface roughness as an expression of the variability of a topographic surface at a given scale, where the scale of analysis is determined by the size of the landforms or geomorphic features of interest. Six techniques for the calculation of surface roughness were selected for an assessment of the parameter`s behavior at different spatial scales and data-set resolutions. Area ratio operated independently of scale, providing consistent results across spatial resolutions. Vector dispersion produced results with increasing roughness and homogenization of terrain at coarser resolutions and larger window sizes. Standard deviation of residual topography highlighted local features and did not detect regional relief. Standard deviation of elevation correctly identified breaks of slope and was good at detecting regional relief. Standard deviation of slope (SD(slope)) also correctly identified smooth sloping areas and breaks of slope, providing the best results for geomorphological analysis. Standard deviation of profile curvature identified the breaks of slope, although not as strongly as SD(slope), and it is sensitive to noise and spurious data. In general, SD(slope) offered good performance at a variety of scales, while the simplicity of calculation is perhaps its single greatest benefit.

Improved likelihood inference for the shape parameter in Weibull regression

We obtain adjustments to the profile likelihood function in Weibull regression models with and without censoring. Specifically, we consider two different modified profile likelihoods: (i) the one proposed by Cox and Reid [Cox, D.R. and Reid, N., 1987, Parameter orthogonality and approximate conditional inference. Journal of the Royal Statistical Society B, 49, 1-39.], and (ii) an approximation to the one proposed by Barndorff-Nielsen [Barndorff-Nielsen, O.E., 1983, On a formula for the distribution of the maximum likelihood estimator. Biometrika, 70, 343-365.], the approximation having been obtained using the results by Fraser and Reid [Fraser, D.A.S. and Reid, N., 1995, Ancillaries and third-order significance. Utilitas Mathematica, 47, 33-53.] and by Fraser et al. [Fraser, D.A.S., Reid, N. and Wu, J., 1999, A simple formula for tail probabilities for frequentist and Bayesian inference. Biometrika, 86, 655-661.]. We focus on point estimation and likelihood ratio tests on the shape parameter in the class of Weibull regression models. We derive some distributional properties of the different maximum likelihood estimators and likelihood ratio tests. The numerical evidence presented in the paper favors the approximation to Barndorff-Nielsen`s adjustment.

Local Influence Under Parameter Constraints

Calculations of local influence curvatures and leverage have been well developed when the parameters are unrestricted. In this article, we discuss the assessment of local influence and leverage under linear equality parameter constraints with extensions to inequality constraints. Using a penalized quadratic function we express the normal curvature of local influence for arbitrary perturbation schemes and the generalized leverage matrix in interpretable forms, which depend on restricted and unrestricted components. The results are quite general and can be applied in various statistical models. In particular, we derive the normal curvature under three useful perturbation schemes for generalized linear models. Four illustrative examples are analyzed by the methodology developed in the article.

Skovgaard`s adjustment to likelihood ratio tests in exponential family nonlinear models

Likelihood ratio tests can be substantially size distorted in small- and moderate-sized samples. In this paper, we apply Skovgaard`s [Skovgaard, I.M., 2001. Likelihood asymptotics. Scandinavian journal of Statistics 28, 3-321] adjusted likelihood ratio statistic to exponential family nonlinear models. We show that the adjustment term has a simple compact form that can be easily implemented from standard statistical software. The adjusted statistic is approximately distributed as X(2) with high degree of accuracy. It is applicable in wide generality since it allows both the parameter of interest and the nuisance parameter to be vector-valued. Unlike the modified profile likelihood ratio statistic obtained from Cox and Reid [Cox, D.R., Reid, N., 1987. Parameter orthogonality and approximate conditional inference. journal of the Royal Statistical Society B49, 1-39], the adjusted statistic proposed here does not require an orthogonal parameterization. Numerical comparison of likelihood-based tests of varying dispersion favors the test we propose and a Bartlett-corrected version of the modified profile likelihood ratio test recently obtained by Cysneiros and Ferrari [Cysneiros, A.H.M.A., Ferrari, S.L.P., 2006. An improved likelihood ratio test for varying dispersion in exponential family nonlinear models. Statistics and Probability Letters 76 (3), 255-265]. (C) 2008 Elsevier B.V. All rights reserved.

Reduction of Models in the Presence of Nuisance Parameters

In many statistical inference problems, there is interest in estimation of only some elements of the parameter vector that defines the adopted model. In general, such elements are associated to measures of location and the additional terms, known as nuisance parameters, to control the dispersion and asymmetry of the underlying distributions. To estimate all the parameters of the model and to draw inferences only on the parameters of interest. Depending on the adopted model, this procedure can be both algebraically is common and computationally very costly and thus it is convenient to reduce it, so that it depends only on the parameters of interest. This article reviews estimation methods in the presence of nuisance parameters and consider some applications in models recently discussed in the literature.

Computational study of the step size parameter of the subgradient optimization method

The subgradient optimization method is a simple and flexible linear programming iterative algorithm. It is much simpler than Newton's method and can be applied to a wider variety of problems. It also converges when the objective function is non-differentiable. Since an efficient algorithm will not only produce a good solution but also take less computing time, we always prefer a simpler algorithm with high quality. In this study a series of step size parameters in the subgradient equation is studied. The performance is compared for a general piecewise function and a specific p-median problem. We examine how the quality of solution changes by setting five forms of step size parameter.

Quantum control of electromagnetically induced transparency dispersion via atomic tunneling in a double-well Bose-Einstein condensate

Electromagnetically induced transparency (EIT) is an important tool for controlling light propagation and nonlinear wave mixing in atomic gases with potential applications ranging from quantum computing to table top tests of general relativity. Here we consider EIT in an atomic Bose-Einstein condensate (BEC) trapped in a double-well potential. A weak probe laser propagates through one of the wells and interacts with atoms in a three-level Lambda configuration. The well through which the probe propagates is dressed by a strong control laser with Rabi frequency Omega(mu), as in standard EIT systems. Tunneling between the wells at the frequency g provides a coherent coupling between identical electronic states in the two wells, which leads to the formation of interwell dressed states. The macroscopic interwell coherence of the BEC wave function results in the formation of two ultranarrow absorption resonances for the probe field that are inside of the ordinary EIT transparency window. We show that these new resonances can be interpreted in terms of the interwell dressed states and the formation of a type of dark state involving the control laser and the interwell tunneling. To either side of these ultranarrow resonances there is normal dispersion with very large slope controlled by g. We discuss prospects for observing these ultranarrow resonances and the corresponding regions of high dispersion experimentally.

Parameter estimation of Poisson generalized linear mixed models based on three different statistical principles : a simulation study

Generalized linear mixed models are flexible tools for modeling non-normal data and are useful for accommodating overdispersion in Poisson regression models with random effects. Their main difficulty resides in the parameter estimation because there is no analytic solution for the maximization of the marginal likelihood. Many methods have been proposed for this purpose and many of them are implemented in software packages. The purpose of this study is to compare the performance of three different statistical principles - marginal likelihood, extended likelihood, Bayesian analysis-via simulation studies. Real data on contact wrestling are used for illustration.

Estudo geotécnico sobre a erodibilidade de solos residuais não saturados

A erodibilidade, particularizada como a susceptibilidade a erosão hídrica por fluxo superficial concentrado, é uma das propriedades de comportamento dos solos de maior complexidade pelo grande número de variáveis intervenientes. Estudada por diferentes áreas do conhecimento (Agronomia, Hidráulica, Geologia de Engenharia e Engenharia Geotécnica), tem no meio geotécnico a maior lacuna na sua quantificação e entendimento dos mecanismos envolvidos. O presente trabalho apresenta um estudo sobre a erodibilidade de solos residuais tropicais e subtropicais não saturados a partir de quatro perfis representativos dos processos erosivos e solos envolvidos na Região Metropolitana de Porto Alegre. Os solos dos principais horizontes de cada um destes perfis foram caracterizados física, química e mineralogicamente. As propriedades de resistência ao cisalhamento e colapsibilidade foram avaliadas por ensaios de cisalhamento direto convencionais e com controle de sucção e por ensaios de colapsibilidade em oedômetros, respectivamente. A erodibilidade foi avaliada em laboratório, diretamente por meio de ensaios de Inderbitzen e indiretamente por diferentes critérios e parâmetros baseados em outras características físicas e propriedades dos solos. A análise conjunta do comportamento dos solos em campo frente a erosão, da avaliação direta e indireta da erodibilidade e das propriedades geomecânicas investigadas conduziram à formulação de uma proposta de abordagem geotécnica para a erodibilidade dos solos residuais tropicais e subtropicais não saturados. Nesta proposta destaca–se a avaliação direta da erodibilidade por ensaios de Inderbitzen e a indicação de solos potencialmente erodíveis baseada no teor de finos, na plasticidade, no parâmetro K da USLE, na Razão de Dispersão de Middleton, na classificação e critério de erodibilidade MCT e na variação da coesão com a saturação pelo parâmetro variação de coesão (Δc) proposto. A proposta de abordagem geotécnica para a previsão da erodibilidade dos solos visa dotar o engenheiro geotécnico de uma ferramenta destinada à avaliação do potencial erosivo dos terrenos antes de uma iniciativa de ocupação urbana ou implantação de qualquer outra obra de engenharia. Esta avaliação é o passo inicial no direcionamento de medidas preventivas e que visem minimizar o impacto da obra ao meio físico natural, no que se refere a erosão hídrica por fluxo superficial concentrado.

Using consumer search cost and loyalty to explain dispersion in banking fees

Pode-se observar uma considerável dispersão entre os preços que diferentes bancos comerciais no Brasil cobram por um mesmo pacote homogêneo de serviços— dispersão esta que é sustentada ao longo do tempo. Em uma tentativa de replicar esta observação empírica, foi desenvolvido um simples modelo que lança mão do arcabouço da literatura de custos de procura (search costs) e que baseia-se também na lealdade por parte dos consumidores. Em seguida, dados de preços referentes ao setor bancário brasileiro são aplicados ao modelo desenvolvido e alguns exercícios empíricos são então realizados. Esses exercícios permitem que: (i) os custos de procura incorridos pelos consumidores sejam estimados, ao fixar-se os valores dos demais parâmetros e (ii) as correspondentes perdas de peso-morto que surgem como consequência dos custos de procura incorridos pelos consumidores sejam também estimadas. Quando apenas 80% da população é livre para buscar por bancos que cobrem menores tarifas, à taxa de juros mensal de 0,5%, o valor estimado do custo de procura médio incorrido pelos consumidores chega a 1805,80 BRL, sendo a correspondente perda de peso-morto média na ordem de 233,71 BRL por consumidor.