Statistical analysis of maximum likelihood estimator images of human brain FDG PET studies

The work presented evaluates the statistical characteristics of regional bias and expected error in reconstructions of real positron emission tomography (PET) data of human brain fluoro-deoxiglucose (FDG) studies carried out by the maximum likelihood estimator (MLE) method with a robust stopping rule, and compares them with the results of filtered backprojection (FBP) reconstructions and with the method of sieves. The task of evaluating radioisotope uptake in regions-of-interest (ROIs) is investigated. An assessment of bias and variance in uptake measurements is carried out with simulated data. Then, by using three different transition matrices with different degrees of accuracy and a components of variance model for statistical analysis, it is shown that the characteristics obtained from real human FDG brain data are consistent with the results of the simulation studies.

The effects of tax deductibility on the mix of property taxes and use charges: an empirical analysis of the spanish case

This paper tests some hypothesis about the determinants of the local tax structure. In particular, we focus on the effects that the property tax deductibility in the national income tax has on the relative use of the property tax and user charges. We deal with the incentive effects that local governments face regarding the different sources of revenue by means of a model in which the local tax structure and the level of public expenditure arise as a result of the maximizing behaviour of local politicians subject to the economic effects of the tax system. We attempt to test the hypothesis developed with data corresponding to a set of Spanish municipalities during the period 1987-9l. We find that tax deductibility provides incentives to raise revenues from the property tax but does not introduce a biass against user charges or in favor of overall spending growth

The effects of tax deductibility on the mix of property taxes and use charges: an empirical analysis of the spanish case

This paper tests some hypothesis about the determinants of the local tax structure. In particular, we focus on the effects that the property tax deductibility in the national income tax has on the relative use of the property tax and user charges. We deal with the incentive effects that local governments face regarding the different sources of revenue by means of a model in which the local tax structure and the level of public expenditure arise as a result of the maximizing behaviour of local politicians subject to the economic effects of the tax system. We attempt to test the hypothesis developed with data corresponding to a set of Spanish municipalities during the period 1987-9l. We find that tax deductibility provides incentives to raise revenues from the property tax but does not introduce a biass against user charges or in favor of overall spending growth

Maximum likelihood Linear Programming Data Fusion for Speaker Recognition

Biometric system performance can be improved by means of data fusion. Several kinds of information can be fused in order to obtain a more accurate classification (identification or verification) of an input sample. In this paper we present a method for computing the weights in a weighted sum fusion for score combinations, by means of a likelihood model. The maximum likelihood estimation is set as a linear programming problem. The scores are derived from a GMM classifier working on a different feature extractor. Our experimental results assesed the robustness of the system in front a changes on time (different sessions) and robustness in front a change of microphone. The improvements obtained were significantly better (error bars of two standard deviations) than a uniform weighted sum or a uniform weighted product or the best single classifier. The proposed method scales computationaly with the number of scores to be fussioned as the simplex method for linear programming.

Hardy’s inequalities for monotone functions on partly ordered measure spaces

We characterize the weighted Hardy inequalities for monotone functions in Rn +. In dimension n = 1, this recovers the standard theory of Bp weights. For n > 1, the result was previously only known for the case p = 1. In fact, our main theorem is proved in the more general setting of partly ordered measure spaces.

Bayes linear spaces

Linear spaces consisting of σ-finite probability measures and infinite measures (improper priors and likelihood functions) are defined. The commutative group operation, called perturbation, is the updating given by Bayes theorem; the inverse operation is the Radon-Nikodym derivative. Bayes spaces of measures are sets of classes of proportional measures. In this framework, basic notions of mathematical statistics get a simple algebraic interpretation. For example, exponential families appear as affine subspaces with their sufficient statistics as a basis. Bayesian statistics, in particular some well-known properties of conjugated priors and likelihood functions, are revisited and slightly extended

On the inefficiency of the restricted maximum likelihood

The restricted maximum likelihood is preferred by many to the full maximumlikelihood for estimation with variance component and other randomcoefficientmodels, because the variance estimator is unbiased. It is shown that thisunbiasednessis accompanied in some balanced designs by an inflation of the meansquared error.An estimator of the cluster-level variance that is uniformly moreefficient than the fullmaximum likelihood is derived. Estimators of the variance ratio are alsostudied.

BadiRate: Estimating Family Turnover Rates by Likelihood-Based Methods

Motivation: The comparative analysis of gene gain and loss rates is critical for understanding the role of natural selection and adaptation in shaping gene family sizes. Studying complete genome data from closely related species allows accurate estimation of gene family turnover rates. Current methods and software tools, however, are not well designed for dealing with certain kinds of functional elements, such as microRNAs or transcription factor binding sites. Results: Here, we describe BadiRate, a new software tool to estimate family turnover rates, as well as the number of elements in internal phylogenetic nodes, by likelihood-based methods and parsimony. It implements two stochastic population models, which provide the appropriate statistical framework for testing hypothesis, such as lineage-specific gene family expansions or contractions. We have assessed the accuracy of BadiRate by computer simulations, and have also illustrated its functionality by analyzing a representative empirical dataset.

BadiRate: estimating family turnover rates by likelihood-based methods

Motivation: The comparative analysis of gene gain and loss rates is critical for understanding the role of natural selection and adaptation in shaping gene family sizes. Studying complete genome data from closely related species allows accurate estimation of gene family turnover rates. Current methods and software tools, however, are not well designed for dealing with certain kinds of functional elements, such as microRNAs or transcription factor binding sites. Results: Here, we describe BadiRate, a new software tool to estimate family turnover rates, as well as the number of elements in internal phylogenetic nodes, by likelihood-based methods and parsimony. It implements two stochastic population models, which provide the appropriate statistical framework for testing hypothesis, such as lineage-specific gene family expansions or contractions. We have assessed the accuracy of BadiRate by computer simulations, and have also illustrated its functionality by analyzing a representative empirical dataset.

Conditional maximum likelihood timing recovery: estimators and bounds

This paper is concerned with the derivation of new estimators and performance bounds for the problem of timing estimation of (linearly) digitally modulated signals. The conditional maximum likelihood (CML) method is adopted, in contrast to the classical low-SNR unconditional ML (UML) formulationthat is systematically applied in the literature for the derivationof non-data-aided (NDA) timing-error-detectors (TEDs). A new CML TED is derived and proved to be self-noise free, in contrast to the conventional low-SNR-UML TED. In addition, the paper provides a derivation of the conditional Cramér–Rao Bound (CRB ), which is higher (less optimistic) than the modified CRB (MCRB)[which is only reached by decision-directed (DD) methods]. It is shown that the CRB is a lower bound on the asymptotic statisticalaccuracy of the set of consistent estimators that are quadratic with respect to the received signal. Although the obtained boundis not general, it applies to most NDA synchronizers proposed in the literature. A closed-form expression of the conditional CRBis obtained, and numerical results confirm that the CML TED attains the new bound for moderate to high Eg/No.

Maximum likelihood estimation of position in GNSS

In this letter, we obtain the Maximum LikelihoodEstimator of position in the framework of Global NavigationSatellite Systems. This theoretical result is the basis of a completelydifferent approach to the positioning problem, in contrastto the conventional two-steps position estimation, consistingof estimating the synchronization parameters of the in-viewsatellites and then performing a position estimation with thatinformation. To the authors’ knowledge, this is a novel approachwhich copes with signal fading and it mitigates multipath andjamming interferences. Besides, the concept of Position–basedSynchronization is introduced, which states that synchronizationparameters can be recovered from a user position estimation. Weprovide computer simulation results showing the robustness ofthe proposed approach in fading multipath channels. The RootMean Square Error performance of the proposed algorithm iscompared to those achieved with state-of-the-art synchronizationtechniques. A Sequential Monte–Carlo based method is used todeal with the multivariate optimization problem resulting fromthe ML solution in an iterative way.

Does land titling matter? The role of land property rights in the war on illicit crops in Colombia

This paper analyzes the role of formalization of land property rights in the war against illicit crops in Colombia. We argue that as a consequence of the increase of state presence and visibility during the period of 2000 and 2009, municipalities with a higher level of formalization of their land property rights saw a greater reduction in the area allocated to illicit crops. We hypothesize that this is due to the increased cost of growing illicit crops on formal land compared to informal, and due to the possibility of obtaining more benets in the newly in- stalled institutional environment when land is formalized. We exploit the variation in the level of formalization of land property rights in a set of municipalities that had their rst cadastral census collected in the period of 1994-2000; this selection procedure guarantees reliable data and an unbiased source of variation. Using fixed effects estimators, we found a signicant negative relationship between the level of formalization of land property rights and the number of hectares allocated to coca crops per municipality. These results remain robust through a number of sensitivity analyses. Our ndings contribute to the growing body of evidence on the positive effects of formal land property rights, and e ective policies in the war on drugs in Colombia.

Effect of diet composition and ration size on key enzyme activities of glycolysis-gluconeogenesis, pentose phosphate pathway and amino acid metabolism in liver of Sparus aurata

The effects of diet composition and ration size on the activities of key enzymes involved in intermediary metabolism were studied in the liver of gilthead sea bream (Sparus aurata). Highcarbohydrate, low-protein diets stimulated 6-phosphofructo 1-kinase (EC 2.7.1.11), pyruvate kinase (EC 2.7.1.40), glucose-6-phosphate dehydrogenase (EC 1.1.1.49) and 6-phosphogluconate dehydrogenase (EC 1.1.1.44) enzyme activities, while they decreased alanine aminotransferase (EC 2.6.1.2) activity. A high degree of correlation was found between food ration size and the activity of the enzymes 6-phosphofructo 1-kinase, pyruvate kinase, glucose-6-phosphate dehydrogenase (positive correlations) and fructose-1,6-bisphosphatase (EC 3.1.3.11) (negative correlation). These correlations matched well with the high correlation also found between ration size and growth rate in starved fish refed for 22 d. Limited feeding (5 g/kg body weight) for 22 d decreased the activities of the key enzymes for glycolysis and lipogenesis, and alanine aminotransferase activity. The findings presented here indicate a high level of metabolic adaptation to both diet type and ration size. In particular, adaptation of enzyme activities to the consumption of a diet with a high carbohydrate level suggests that a carnivorous fish like Sparus aurata can tolerate partial replacement of protein by carbohydrate in the commercial diets supplied in culture. The relationship between enzyme activities, ration size and fish growth indicates that the enzymes quickly respond to dietary manipulations of cultured fish.

Effect of diet composition and ration size on key enzyme activities of glycolysis-gluconeogenesis, pentose phosphate pathway and amino acid metabolism in liver of Sparus aurata

The effects of diet composition and ration size on the activities of key enzymes involved in intermediary metabolism were studied in the liver of gilthead sea bream (Sparus aurata). Highcarbohydrate, low-protein diets stimulated 6-phosphofructo 1-kinase (EC 2.7.1.11), pyruvate kinase (EC 2.7.1.40), glucose-6-phosphate dehydrogenase (EC 1.1.1.49) and 6-phosphogluconate dehydrogenase (EC 1.1.1.44) enzyme activities, while they decreased alanine aminotransferase (EC 2.6.1.2) activity. A high degree of correlation was found between food ration size and the activity of the enzymes 6-phosphofructo 1-kinase, pyruvate kinase, glucose-6-phosphate dehydrogenase (positive correlations) and fructose-1,6-bisphosphatase (EC 3.1.3.11) (negative correlation). These correlations matched well with the high correlation also found between ration size and growth rate in starved fish refed for 22 d. Limited feeding (5 g/kg body weight) for 22 d decreased the activities of the key enzymes for glycolysis and lipogenesis, and alanine aminotransferase activity. The findings presented here indicate a high level of metabolic adaptation to both diet type and ration size. In particular, adaptation of enzyme activities to the consumption of a diet with a high carbohydrate level suggests that a carnivorous fish like Sparus aurata can tolerate partial replacement of protein by carbohydrate in the commercial diets supplied in culture. The relationship between enzyme activities, ration size and fish growth indicates that the enzymes quickly respond to dietary manipulations of cultured fish.

Indirect likelihood inference (revised)

Standard indirect Inference (II) estimators take a given finite-dimensional statistic, Z_{n} , and then estimate the parameters by matching the sample statistic with the model-implied population moment. We here propose a novel estimation method that utilizes all available information contained in the distribution of Z_{n} , not just its first moment. This is done by computing the likelihood of Z_{n}, and then estimating the parameters by either maximizing the likelihood or computing the posterior mean for a given prior of the parameters. These are referred to as the maximum indirect likelihood (MIL) and Bayesian Indirect Likelihood (BIL) estimators, respectively. We show that the IL estimators are first-order equivalent to the corresponding moment-based II estimator that employs the optimal weighting matrix. However, due to higher-order features of Z_{n} , the IL estimators are higher order efficient relative to the standard II estimator. The likelihood of Z_{n} will in general be unknown and so simulated versions of IL estimators are developed. Monte Carlo results for a structural auction model and a DSGE model show that the proposed estimators indeed have attractive finite sample properties.