A novel MAP-MRF approach for multispectral image contextual classification using combination of suboptimal iterative algorithms

In this paper we present a novel approach for multispectral image contextual classification by combining iterative combinatorial optimization algorithms. The pixel-wise decision rule is defined using a Bayesian approach to combine two MRF models: a Gaussian Markov Random Field (GMRF) for the observations (likelihood) and a Potts model for the a priori knowledge, to regularize the solution in the presence of noisy data. Hence, the classification problem is stated according to a Maximum a Posteriori (MAP) framework. In order to approximate the MAP solution we apply several combinatorial optimization methods using multiple simultaneous initializations, making the solution less sensitive to the initial conditions and reducing both computational cost and time in comparison to Simulated Annealing, often unfeasible in many real image processing applications. Markov Random Field model parameters are estimated by Maximum Pseudo-Likelihood (MPL) approach, avoiding manual adjustments in the choice of the regularization parameters. Asymptotic evaluations assess the accuracy of the proposed parameter estimation procedure. To test and evaluate the proposed classification method, we adopt metrics for quantitative performance assessment (Cohen`s Kappa coefficient), allowing a robust and accurate statistical analysis. The obtained results clearly show that combining sub-optimal contextual algorithms significantly improves the classification performance, indicating the effectiveness of the proposed methodology. (C) 2010 Elsevier B.V. All rights reserved.

Local influence for Student-t partially linear models

In this paper we extend partial linear models with normal errors to Student-t errors Penalized likelihood equations are applied to derive the maximum likelihood estimates which appear to be robust against outlying observations in the sense of the Mahalanobis distance In order to study the sensitivity of the penalized estimates under some usual perturbation schemes in the model or data the local influence curvatures are derived and some diagnostic graphics are proposed A motivating example preliminary analyzed under normal errors is reanalyzed under Student-t errors The local influence approach is used to compare the sensitivity of the model estimates (C) 2010 Elsevier B V All rights reserved

An integrated molecular map of yellow passion fruit based on simultaneous maximum-likelihood estimation of linkage and linkage phases

The development of genetic maps for auto-incompatible species, such as the yellow passion fruit (Passiflora edulis Sims f.flavicarpa Deg.) is restricted due to the unfeasibility of obtaining traditional mapping populations based on inbred lines. For this reason, yellow passion fruit linkage maps were generally constructed using a strategy known as two-way pseudo-testeross, based on monoparental dominant markers segregating in a 1:1 fashion. Due to the lack of information from these markers in one of the parents, two individual (parental) maps were obtained. However, integration of these maps is essential, and biparental markers can be used for such an operation. The objective of our study was to construct an integrated molecular map for a full-sib population of yellow passion fruit combining different loci configuration generated from amplified fragment length polymorphisms (AFLPs) and microsatellite markers and using a novel approach based on simultaneous maximum-likelihood estimation of linkage and linkage phases, specially designed for outcrossing species. Of the total number of loci, approximate to 76%, 21%, 0.7%, and 2.3% did segregate in 1:1, 3:1, 1:2:1, and 1:1:1:1 ratios, respectively. Ten linkage groups (LGs) were established with a logarithm of the odds (LOD) score >= 5.0 assuming a recombination fraction : <= 0.35. On average, 24 markers were assigned per LG, representing a total map length of 1687 cM, with a marker density of 6.9 cM. No markers were placed as accessories on the map as was done with previously constructed individual maps.

Improved maximum likelihood estimators in a heteroskedastic errors-in-variables model

This paper develops a bias correction scheme for a multivariate heteroskedastic errors-in-variables model. The applicability of this model is justified in areas such as astrophysics, epidemiology and analytical chemistry, where the variables are subject to measurement errors and the variances vary with the observations. We conduct Monte Carlo simulations to investigate the performance of the corrected estimators. The numerical results show that the bias correction scheme yields nearly unbiased estimates. We also give an application to a real data set.

A matrix formula for the skewness of maximum likelihood estimators

We give a general matrix formula for computing the second-order skewness of maximum likelihood estimators. The formula was firstly presented in a tensorial version by Bowman and Shenton (1998). Our matrix formulation has numerical advantages, since it requires only simple operations on matrices and vectors. We apply the second-order skewness formula to a normal model with a generalized parametrization and to an ARMA model. (c) 2010 Elsevier B.V. All rights reserved.

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

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.

A note on the likelihood and moments of the skew-normal distribution

In this paper an alternative approach to the one in Henze (1986) is proposed for deriving the odd moments of the skew-normal distribution considered in Azzalini (1985). The approach is based on a Pascal type triangle, which seems to greatly simplify moments computation. Moreover, it is shown that the likelihood equation for estimating the asymmetry parameter in such model is generated as orthogonal functions to the sample vector. As a consequence, conditions for a unique solution of the likelihood equation are established, which seem to hold in more general setting.

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.

Signed likelihood ratio tests in the Birnbaum-Saunders regression model

The Birnbaum-Saunders regression model is becoming increasingly popular in lifetime analyses and reliability studies. In this model, the signed likelihood ratio statistic provides the basis for testing inference and construction of confidence limits for a single parameter of interest. We focus on the small sample case, where the standard normal distribution gives a poor approximation to the true distribution of the statistic. We derive three adjusted signed likelihood ratio statistics that lead to very accurate inference even for very small samples. Two empirical applications are presented. (C) 2010 Elsevier B.V. All rights reserved.

Likelihood ratio tests for variance components in linear mixed models

Although the asymptotic distributions of the likelihood ratio for testing hypotheses of null variance components in linear mixed models derived by Stram and Lee [1994. Variance components testing in longitudinal mixed effects model. Biometrics 50, 1171-1177] are valid, their proof is based on the work of Self and Liang [1987. Asymptotic properties of maximum likelihood estimators and likelihood tests under nonstandard conditions. J. Amer. Statist. Assoc. 82, 605-610] which requires identically distributed random variables, an assumption not always valid in longitudinal data problems. We use the less restrictive results of Vu and Zhou [1997. Generalization of likelihood ratio tests under nonstandard conditions. Ann. Statist. 25, 897-916] to prove that the proposed mixture of chi-squared distributions is the actual asymptotic distribution of such likelihood ratios used as test statistics for null variance components in models with one or two random effects. We also consider a limited simulation study to evaluate the appropriateness of the asymptotic distribution of such likelihood ratios in moderately sized samples. (C) 2008 Elsevier B.V. All rights reserved.

Maximum inhibitory dilution of mouthwashes containing chlorhexidine and polyhexamethylene biguanide against salivary staphylococcus aureus

OBJECTIVE: The aim of the present study was to determine the in vitro maximum inhibitory dilution (MID) of two chlorhexidinebased oral mouthwashes (CHX): Noplak®, Periogard®, and one polyhexamethylene biguanide-based mouthwash (PHMB): Sanifill Premium® against 28 field Staphylococcus aureus strains using the agar dilution method. MATERIALS AND METHODS: For each product, decimal dilutions ranging from 1/10 to 1/655,360 were prepared in distilled water and added to Mueller Hinton Agar culture medium. After homogenization, the culture medium was poured onto Petri dishes. Strains were inoculated using a Steers multipoint inoculator and dishes were incubated at 37ºC for 24hours. For reading, MID was considered as the maximum dilution of the mouthwash still capable of inhibiting microbial growth. RESULTS: Sanifill Premium® inhibited the growth of all strains at 1/40 dilution and of 1 strain at 1/80 dilution. Noplak® inhibited the growth of 23 strains at 1/640 dilution and of all 28 strains at 1/320 dilution. Periogard® showed inhibited growth of 7 strains at 1/640 dilution and of all 28 strains at 1/320 dilution. Data were submitted to Kruskal-Wallis statistical test, showing significant differences between the mouthwashes evaluated (p<0.05). No significant difference was found between Noplak® and Periogard® (p>0.05). Sanifill Premium® was the least effective (p<0.05). CONCLUSION: It was concluded that CHX-based mouthwashes present better antimicrobial activity against S. Aureus than the PHMB-based mouthwash.

Determination of the maximum inhibitory dilution of cetylpyridinium chloride-based mouthwashes against staphylococcus aureus: an in vitro study

The aim of this in vitro study was to determine the maximum inhibitory dilution (MID) of four cetylpyridinium chloride (CPC)-based mouthwashes: CPC+Propolis, CPC+Malva, CPC+Eucaliptol+Juá+Romã+Propolis (Natural Honey®) and CPC (Cepacol®), against 28 Staphylococcus aureus field strains, using the agar dilution method. Decimal dilutions ranging from 1/10 to 1/655,360 were prepared and added to Mueller Hinton Agar. Strains were inoculated using Steers multipoint inoculator. The inocula were seeded onto the surface of the culture medium in Petri dishes containing different dilutions of the mouthwashes. The dishes were incubated at 37ºC for 24 h. For readings, the MID was considered as the maximum dilution of mouthwash still capable of inhibiting microbial growth. The obtained data showed that CPC+Propolis had antimicrobial activity against 27 strains at 1/320 dilution and against all 28 strains at 1/160 dilution, CPC+Malva inhibited the growth of all 28 strains at 1/320 dilution, CPC+Eucaliptol+Juá+Romã+Propolis inhibited the growth of 2 strains at 1/640 dilution and all 28 strains at 1/320 dilution, and Cepacol® showed antimicrobial activity against 3 strains at 1/320 dilution and against all 28 strains at 1/160 dilution. Data were submitted to Kruskal-Wallis test, showing that the MID of Cepacol® was lower than that determined for the other products (p<0.05). In conclusion, CPC-mouthwashes showed antimicrobial activity against S. aureus and the addition of other substances to CPC improved its antimicrobial effect.

Inclusão da epistasia em modelo de avaliação genética de bovinos de corte compostos

Dados de bovinos compostos foram analisados para avaliar o efeito da epistasia nos modelos de avaliação genética. As características analisadas foram os pesos aos 205 (P205) e 390 dias (P390) e perímetro escrotal aos 390 dias (PE390). As análises foram realizadas pela metodologia de máxima verossimilhança considerando-se dois modelos: o modelo 1 incluiu como covariáveis os efeitos aditivos diretos e maternos, e os não aditivos das heterozigoses para os efeitos diretos e para o materno total, e o modelo 2 considerou também o efeito direto de epistasia. Para comparação dos modelos, foram utilizados o critério de informação de Akaike (AIC) e o critério de informação Bayesiano de Schwartz (BIC), e o teste de razão de verossimilhança. A inclusão da epistasia no modelo de avaliação genética pouco alterou as estimativas de componentes de (co)variâncias genéticas aditivas e, consequentemente, as herdabilidades. O teste de verossimilhança e o critério de Akaike sugeriram que o modelo 2, que inclui a epistasia, apresentou maior aderência aos dados para todas as características analisadas. O critério BIC indicou este modelo como o melhor apenas para P205. Para análise genética dessa população, o modelo que considerou o efeito de epistasia foi o mais adequado.

Thaptomys Thomas 1915 (Rodentia, Sigmodontinae, Akodontini) with karyotypes 2n = 50, FN = 48, and 2n = 52, FN = 52: two monophyletic lineages recovered by molecular phylogeny

A novel karyotype with 2n = 50, FN = 48, was described for specimens of Thaptomys collected at Una, State of Bahia, Brazil, which are morphologically indistinguishable from Thaptomys nigrita, 2n = 52, FN = 52, found in other localities. It was hence proposed that the 2n = 50 karyotype could belong to a distinct species, cryptic of Thaptomys nigrita, once chromosomal rearrangements observed, along with the geographic distance, might represent a reproductive barrier between both forms. Phylogenetic analyses using maximum parsimony and maximum likelihood based on partial cytochrome b sequences with 1077 bp were performed, attempting to establish the relationships among the individuals with distinct karyotypes along the geographic distribution of the genus; the sample comprised 18 karyotyped specimens of Thaptomys, encompassing 15 haplotypes, from eight different localities of the Atlantic Rainforest. The intra-generic relationships corroborated the distinct diploid numbers, once both phylogenetic reconstructions recovered two monophyletic lineages, a northeastern clade grouping the 2n = 50 and a southeastern clade with three subclades, grouping the 2n = 52 karyotype. The sequence divergence observed between their individuals ranged from 1.9% to 3.5%.

PENCALC: a program for penetrance estimation in autosomal dominant diseases

We present a computer program developed for estimating penetrance rates in autosomal dominant diseases by means of family kinship and phenotype information contained within the pedigrees. The program also determines the exact 95% credibility interval for the penetrance estimate. Both executable (PenCalc for Windows) and web versions (PenCalcWeb) of the software are available. The web version enables further calculations, such as heterozygosity probabilities and assessment of offspring risks for all individuals in the pedigrees. Both programs can be accessed and down-loaded freely at the home-page address http://www.ib.usp.br/~otto/software.htm.