38 resultados para Likelihood Functions


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We develop and describe continuous and discrete transforms of class functions on a compact semisimple, but not simple, Lie group G as their expansions into series of special functions that are invariant under the action of the even subgroup of the Weyl group of G. We distinguish two cases of even Weyl groups-one is the direct product of even Weyl groups of simple components of G and the second is the full even Weyl group of G. The problem is rather simple in two dimensions. It is much richer in dimensions greater than two-we describe in detail E-transforms of semisimple Lie groups of rank 3.

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In [H. Brezis, A. Friedman, Nonlinear parabolic equations involving measures as initial conditions, J. Math. Pure Appl. (9) (1983) 73-97.] Brezis and Friedman prove that certain nonlinear parabolic equations, with the delta-measure as initial data, have no solution. However in [J.F. Colombeau, M. Langlais, Generalized solutions of nonlinear parabolic equations with distributions as initial conditions, J. Math. Anal. Appl (1990) 186-196.] Colombeau and Langlais prove that these equations have a unique solution even if the delta-measure is substituted by any Colombeau generalized function of compact support. Here we generalize Colombeau and Langlais` result proving that we may take any generalized function as the initial data. Our approach relies on recent algebraic and topological developments of the theory of Colombeau generalized functions and results from [J. Aragona, Colombeau generalized functions on quasi-regular sets, Publ. Math. Debrecen (2006) 371-399.]. (C) 2009 Elsevier Ltd. All rights reserved.

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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.

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Birnbaum and Saunders (1969a) introduced a probability distribution which is commonly used in reliability studies For the first time based on this distribution the so-called beta-Birnbaum-Saunders distribution is proposed for fatigue life modeling Various properties of the new model including expansions for the moments moment generating function mean deviations density function of the order statistics and their moments are derived We discuss maximum likelihood estimation of the model s parameters The superiority of the new model is illustrated by means of three failure real data sets (C) 2010 Elsevier B V All rights reserved

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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.

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We propose a likelihood ratio test ( LRT) with Bartlett correction in order to identify Granger causality between sets of time series gene expression data. The performance of the proposed test is compared to a previously published bootstrapbased approach. LRT is shown to be significantly faster and statistically powerful even within non- Normal distributions. An R package named gGranger containing an implementation for both Granger causality identification tests is also provided.

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In this paper we obtain asymptotic expansions up to order n(-1/2) for the nonnull distribution functions of the likelihood ratio, Wald, score and gradient test statistics in exponential family nonlinear models (Cordeiro and Paula, 1989), under a sequence of Pitman alternatives. The asymptotic distributions of all four statistics are obtained for testing a subset of regression parameters and for testing the dispersion parameter, thus generalising the results given in Cordeiro et al. (1994) and Ferrari et al. (1997). We also present Monte Carlo simulations in order to compare the finite-sample performance of these tests. (C) 2010 Elsevier B.V. All rights reserved.

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Mitochondrial transcription factor A (TFAM) is an essential component of mitochondrial nucleoids TFAM plays an important role in mitochondrial transcription and replication TFAM has been previously reported to inhibit nucleotide excision repair (NER) in vitro but NER has not yet been detected in mitochondria, whereas base excision repair (BER) has been comprehensively characterized in these organelles The BER proteins are associated with the inner membrane in mitochondria and thus with the mitochondrial nucleoid, where TFAM is also situated However, a function for TFAM in BER has not yet been investigated This study examines the role of TFAM in BER In vitro studies with purified recombinant TFAM indicate that it preferentially binds to DNA containing 8-oxoguanines, but not to abasic sites, uracils, or a gap in the sequence TFAM inhibited the in vitro incision activity of 8-oxoguanine DNA glycosylase (OGG1), uracil-DNA glycosylase (UDG), apurinic endonuclease 1 (APE1), and nucleotide incorporation by DNA polymerase gamma (pol gamma) On the other hand, a DNA binding-defective TFAM mutant, L58A, showed less inhibition of BER in vitro Characterization of TFAM knockdown (KD) cells revealed that these lysates had higher 8oxoG incision activity without changes in alpha OGG1 protein levels TFAM KD cells had mild resistance to menadione and increased damage accumulation in the mtDNA when compared to the control cells In addition, we found that the tumor suppressor p53, which has been shown to interact with and alter the DNA binding activity of TFAM, alleviates TFAM-Induced inhibition of BER proteins Together, the results suggest that TFAM modulates BER in mitochondria by virtue of its DNA binding activity and protein interactions Published by Elsevier B V