Comparison of parametric and nonparametric methods to map oligogenes by linkage

A sample of 95 sib pairs affected with insulin-dependent diabetes and typed with their normal parents for 28 markers on chromosome 6 has been analyzed by several methods. When appropriate parameters are efficiently estimated, a parametric model is equivalent to the β model, which is superior to nonparametric alternatives both in single point tests (as found previously) and in multipoint tests. Theory is given for meta-analysis combined with allelic association, and problems that may be associated with errors of map location and/or marker typing are identified. Reducing by multipoint analysis the number of association tests in a dense map can give a 3-fold reduction in the critical lod, and therefore in the cost of positional cloning.

On the accuracy of Latin American trade statistics: A nonparametric test for 1925

This paper proposes a nonparametric test in order to establish the level of accuracy of theforeign trade statistics of 17 Latin American countries when contrasted with the trade statistics of the main partners in 1925. The Wilcoxon Matched-Pairs Ranks test is used to determine whether the differences between the data registered by exporters and importers are meaningful, and if so, whether the differences are systematic in any direction. The paper tests for the reliability of the data registered for two homogeneous products, petroleum and coal, both in volume and value. The conclusion of the several exercises performed is that we cannot accept the existence of statistically significant differences between the data provided by the exporters and the registered by the importing countries in most cases. The qualitative historiography of Latin American describes its foreign trade statistics as mostly unusable. Our quantitative results contest this view.

A nonparametric method for the measurement of size diversity with emphasis on data standardization

The most suitable method for estimation of size diversity is investigated. Size diversity is computed on the basis of the Shannon diversity expression adapted for continuous variables, such as size. It takes the form of an integral involving the probability density function (pdf) of the size of the individuals. Different approaches for the estimation of pdf are compared: parametric methods, assuming that data come from a determinate family of pdfs, and nonparametric methods, where pdf is estimated using some kind of local evaluation. Exponential, generalized Pareto, normal, and log-normal distributions have been used to generate simulated samples using estimated parameters from real samples. Nonparametric methods include discrete computation of data histograms based on size intervals and continuous kernel estimation of pdf. Kernel approach gives accurate estimation of size diversity, whilst parametric methods are only useful when the reference distribution have similar shape to the real one. Special attention is given for data standardization. The division of data by the sample geometric mean is proposedas the most suitable standardization method, which shows additional advantages: the same size diversity value is obtained when using original size or log-transformed data, and size measurements with different dimensionality (longitudes, areas, volumes or biomasses) may be immediately compared with the simple addition of ln k where kis the dimensionality (1, 2, or 3, respectively). Thus, the kernel estimation, after data standardization by division of sample geometric mean, arises as the most reliable and generalizable method of size diversity evaluation

Exact Nonparametric Two-Sample Homogeneity Tests for Possibly Discrete Distributions.

In this paper, we study several tests for the equality of two unknown distributions. Two are based on empirical distribution functions, three others on nonparametric probability density estimates, and the last ones on differences between sample moments. We suggest controlling the size of such tests (under nonparametric assumptions) by using permutational versions of the tests jointly with the method of Monte Carlo tests properly adjusted to deal with discrete distributions. We also propose a combined test procedure, whose level is again perfectly controlled through the Monte Carlo test technique and has better power properties than the individual tests that are combined. Finally, in a simulation experiment, we show that the technique suggested provides perfect control of test size and that the new tests proposed can yield sizeable power improvements.

Parametric and Nonparametric Approaches to Price and Tax Reform.

In the analysis of tax reform, when equity is traded off against efficiency, the measurement of the latter requires us to know how tax-induced price changes affect quantities supplied and demanded. in this paper, we present various econometric procedures for estimating how taxes affect demand.

Bayesian nonparametric latent variable models

L’un des problèmes importants en apprentissage automatique est de déterminer la complexité du modèle à apprendre. Une trop grande complexité mène au surapprentissage, ce qui correspond à trouver des structures qui n’existent pas réellement dans les données, tandis qu’une trop faible complexité mène au sous-apprentissage, c’est-à-dire que l’expressivité du modèle est insuffisante pour capturer l’ensemble des structures présentes dans les données. Pour certains modèles probabilistes, la complexité du modèle se traduit par l’introduction d’une ou plusieurs variables cachées dont le rôle est d’expliquer le processus génératif des données. Il existe diverses approches permettant d’identifier le nombre approprié de variables cachées d’un modèle. Cette thèse s’intéresse aux méthodes Bayésiennes nonparamétriques permettant de déterminer le nombre de variables cachées à utiliser ainsi que leur dimensionnalité. La popularisation des statistiques Bayésiennes nonparamétriques au sein de la communauté de l’apprentissage automatique est assez récente. Leur principal attrait vient du fait qu’elles offrent des modèles hautement flexibles et dont la complexité s’ajuste proportionnellement à la quantité de données disponibles. Au cours des dernières années, la recherche sur les méthodes d’apprentissage Bayésiennes nonparamétriques a porté sur trois aspects principaux : la construction de nouveaux modèles, le développement d’algorithmes d’inférence et les applications. Cette thèse présente nos contributions à ces trois sujets de recherches dans le contexte d’apprentissage de modèles à variables cachées. Dans un premier temps, nous introduisons le Pitman-Yor process mixture of Gaussians, un modèle permettant l’apprentissage de mélanges infinis de Gaussiennes. Nous présentons aussi un algorithme d’inférence permettant de découvrir les composantes cachées du modèle que nous évaluons sur deux applications concrètes de robotique. Nos résultats démontrent que l’approche proposée surpasse en performance et en flexibilité les approches classiques d’apprentissage. Dans un deuxième temps, nous proposons l’extended cascading Indian buffet process, un modèle servant de distribution de probabilité a priori sur l’espace des graphes dirigés acycliques. Dans le contexte de réseaux Bayésien, ce prior permet d’identifier à la fois la présence de variables cachées et la structure du réseau parmi celles-ci. Un algorithme d’inférence Monte Carlo par chaîne de Markov est utilisé pour l’évaluation sur des problèmes d’identification de structures et d’estimation de densités. Dans un dernier temps, nous proposons le Indian chefs process, un modèle plus général que l’extended cascading Indian buffet process servant à l’apprentissage de graphes et d’ordres. L’avantage du nouveau modèle est qu’il admet les connections entres les variables observables et qu’il prend en compte l’ordre des variables. Nous présentons un algorithme d’inférence Monte Carlo par chaîne de Markov avec saut réversible permettant l’apprentissage conjoint de graphes et d’ordres. L’évaluation est faite sur des problèmes d’estimations de densité et de test d’indépendance. Ce modèle est le premier modèle Bayésien nonparamétrique permettant d’apprendre des réseaux Bayésiens disposant d’une structure complètement arbitraire.

Nonparametric tests of collectively rational consumption behavior: an integer programming procedure

We present an IP-based nonparametric (revealed preference) testing procedure for rational consumption behavior in terms of general collective models, which include consumption externalities and public consumption. An empirical application to data drawn from the Russia Longitudinal Monitoring Survey (RLMS) demonstrates the practical usefulness of the procedure. Finally, we present extensions of the testing procedure to evaluate the goodness-of-…t of the collective model subject to testing, and to quantify and improve the power of the corresponding collective rationality tests.

Semiochemicals and social signaling in the wild European rabbit in Australia: II. Variations in chemical composition of chin gland secretion across sampling sites

The volatile components of the chin gland secretion of the wild European rabbit, Oryctolagus cuniculus (L.), were investigated with the use of gas chromatography. Studies of the chemical nature of this secretion by previous workers demonstrated that it was important in the maintenance of social structure in this species. This study identified 34 different volatile components that consist primarily of aromatic and aliphatic hydrocarbons. Especially common are a series of alkyl-substituted benzene derivatives that provide most of the compound diversity in the secretion. Samples of chin gland secretion collected from animals at three different geographical locations, separated by more than 100 km, showed significant differences in composition. This work suggests that variation among populations needs to be considered when undertaking semiochemical research. Alternate nonparametric methods are also used for the analysis of chromatographic data.

Biofilm Dissolution and Cleaning Ability of Different Irrigant Solutions on Intraorally Infected Dentin

Introduction: The aim of this study was to evaluate the biofilm dissolution and cleaning ability of different irrigant solutions on intraorally infected dentin. Methods: One hundred twenty bovine dentin specimens were infected intraorally by using a removable orthodontic device. Thirty samples were used for each irrigant solution: 2% chlorhexidine and 1%, 2.5%, and 5.25% sodium hypochlorite (NaOCl). The solutions were used for 5, 15, and 30 minutes and at 2 experimental volumes, 500 mu L and 1 mL. The samples were stained by using acridine orange dye before and after the experiments and evaluated by using a confocal microscope. The percentage of biofilm, isolated cells, and noncolonized dentin was measured by using a grid system. Differences in the reduction or increase of the studied parameters were assessed by using nonparametric methods (P < .05). Results: The higher values of biofilm dissolution and noncolonized dentin were found in the 30-minute NaOCl group and in the 5-minute and 15-minute groups of 5.25% NaOCL. The use of 2% chlorhexidine solution did not improve the biofilm dissolution or increase the cleaning of the dentin in comparison with the NaOCl solutions (P < .05). Conclusions: Two percent chlorhexidine does not dissolve the biofilms. Thirty minutes of NaOCl are necessary to have higher values of biofilm dissolution and to increase the cleaning of the dentin independently of the concentration in comparison with the 5-minute and 15-minute contact times. (J Endod 2011;37:1134-1138)

Validação da antropometria e ultrassonografia do braço, para medição dos respectivos compartimentos, em lactentes nascidos pré-termo : contributo para a avaliação corporal do recem-nascido e do lactente

RESUMO: Contexto: Indicadores fidedignos da composição corporal são importantes na orientação das estratégias nutricionais de recém-nascidos e pequenos lactentes submetidos a cuidados intensivos. O braço é uma região acessível para avaliar a composição corporal regional, pela medida dos seus compartimentos. A antropometria e a ultrassonografia (US) são métodos não invasivos, relativamente económicos, que podem ser usados à cabeceira do paciente na medição desses compartimentos, embora esses métodos não tenham ainda sido validados neste subgrupo etário. A ressonância magnética (RM) pode ser usada como método de referência na validação da medição dos compartimentos do braço. Objectivo: Validar em lactentes pré-termo, as medidas do braço por antropometria e por US. Métodos: Foi estudada uma coorte de recém-nascidos admitidos consecutivamente na unidade de cuidados intensivos neonatais, com  33 semanas de idade de gestação e peso adequado para a mesma, sem anomalias congénitas major e não submetidas a diuréticos ou oxigenoterapia no momento da avaliação. Nas vésperas da alta, foram efectuadas medições do braço, com ocultação, pelos métodos antropométrico, ultrassonográfico e RM. As medidas antropométricas directas foram: peso (P), comprimento (C), perímetro cefálico (PC), perímetro braquial (PB) e prega cutânea tricipital (PT). As área braquial total, área muscular (AM) e área adiposa foram calculadas pelos métodos de Jeliffee & Jeliffee e de Rolland-Cachera. Utilizando uma sonda PSH-7DLT de 7 Hz no ecógrafo Toshiba SSH 140A foram medidos os perímetros braquial e muscular e calculadas automaticamente as áreas braquial e muscular, sendo a área adiposa obtida por subtracção. Como método de referência foi utilizada a RM – Philips Gyroscan ACS-NT, Power-Track 1000 ®, 1.5 Tesla com uma antena de quadratura do joelho. Na análise estatística foram utilizados os métodos paramétricos e não paramétricos, conforme adequado. Resultados: Foram incluídas 30 crianças, nascidas com ( ±DP) 30.7 ±1.9 semanas de gestação, pesando 1380 ±325g, as quais foram avaliadas às 35.4 ±1.1 semanas de idade corrigida, quando pesavam 1786 ±93g. Nenhuma das medidas antropométricas, individualmente, constitui um indicador aceitável (r2 <0.5) das medições por RM. A melhor e mais simples equação alternativa encontrada é a que estima a AM (r2 = 0.56), derivada dos resultados da análise de regressão múltipla: AMRM = (P x 0.17) + (PB x 5.2) – (C x 6) – 150, sendo o P expresso em g, o C e o PB em cm. Nenhuma das medidas ultrassonográficas constitui um indicador aceitável (r2 <0.4) das medições por RM. Conclusões: A antropometria e as medidas ultrassonográficas do braço não são indicadores fidedignos da composição corporal regional em lactentes pré-termo, adequados para a idade de gestação.----------ABSTRACT: Background: Accurate predictors for body composition are valuable tools guiding nutritional strategies in infants needing intensive care. The upper-arm is a part of the body that is easily accessible and convenient for assessing the regional body composition, throughout the assessment of their compartments. Anthropometry and by ultrasonography (US) are noninvasive and relatively nonexpensive methods for bedside assessment of the upper-arm compartments. However, these methods have not yet been validated in infants. Magnetic resonance imaging (MRI) may be used as gold standard to validate the measurements of the upper-arm compartments. Objective: To validate the upper-arm measurements by anthropometry and by US in preterm infants. Methods: A cohort of neonates consecutively admitted at the neonatal intensive care unit, appropriate for gestational age, with  33 weeks, without major congenital abnormalities and not subjected to diuretics or oxygen therapy, was assessed. Before the discharge, the upper-arm was blindly measured by anthropometry, US and MRI. The direct anthropometric parameters measured were: weight (W), length (L), head circumference (HC), mid-arm circumference (MAC), and tricipital skinfold thickness. The arm area (AA), arm muscle area (AMA) and arm fat area were calculated applying the methods proposed by Jeliffee & Jeliffee and by Rolland-Cachera. Using the sonolayer Toshiba SSH 140A and the probe PSH-7DLT 7Hz, the arm and muscle perimeters were measured by US, the arm and muscle areas included were automatically calculated, and the fat area was calculated by subtraction. The MR images were acquired on a 1.5-T Philips Gyroscan ACS-NT, Power-Track 1000 scanner, and a knee coil was chosen for the upper-arm measurements. For statistical analysis parametric and nonparametric methods were used as appropriate. Results: Thirty infants born with ( ±SD) 30.7 ±1.9 weeks of gestational age and weighing 1380 ±325g were included in the study; they were assessed at 35.4 ±1.1 weeks of corrected age, weighing 1786 ±93g. None of the anthropometric measurements are individually acceptable (r2 <0.5) for prediction of the measurements obtained by MRI. The best and simple alternative equation found is the equation for prediction of the AMA (r2 = 0.56), derived from the results of multiple regression analysis: AMARM = (W x 0.17) + (MAC x 5.2) – (L x 6) – 150, being the W expressed in g, and L and MAC in cm. None of the ultrasonographic measurements are acceptable (r2 <0.5) predictors for the measurements obtained by MRI. Conclusions: The measurements of the upper-arm by anthropometry and by US are not accurate predictors for the regional body composition in preterm appropriate for gestational age infants.

A Data mining approach to indirect inference

Consider a model with parameter phi, and an auxiliary model with parameter theta. Let phi be a randomly sampled from a given density over the known parameter space. Monte Carlo methods can be used to draw simulated data and compute the corresponding estimate of theta, say theta_tilde. A large set of tuples (phi, theta_tilde) can be generated in this manner. Nonparametric methods may be use to fit the function E(phi|theta_tilde=a), using these tuples. It is proposed to estimate phi using the fitted E(phi|theta_tilde=theta_hat), where theta_hat is the auxiliary estimate, using the real sample data. This is a consistent and asymptotically normally distributed estimator, under certain assumptions. Monte Carlo results for dynamic panel data and vector autoregressions show that this estimator can have very attractive small sample properties. Confidence intervals can be constructed using the quantiles of the phi for which theta_tilde is close to theta_hat. Such confidence intervals are found to have very accurate coverage.

Changing Diets in China’s Cities: Empirical Fact or Urban Legend, November 2006

China’s economic reforms, which began in 1978, resulted in remarkable income growth, and urban Chinese consumers have responded by dramatically increasing their consumption of meat, other livestock products, and fruits and by decreasing consumption of grain-based foods. Economic prosperity, a growing openness to international markets, and domestic policy reforms have changed the food marketing environment for Chinese consumers and may have contributed to shifts in consumer preferences. The objective of this paper is to uncover evidence of structural change in food consumption among urban residents in China. Both parametric and nonparametric methods are used to test for structural change in aggregate household data from 1981 to 2004. The tests provided a reasonably clear picture of changing food consumption over the study period.

The Seemingly Unrelated Dynamic Cointegration Regression Model and Testing for Purching Power Parity.

This paper studies seemingly unrelated linear models with integrated regressors and stationary errors. By adding leads and lags of the first differences of the regressors and estimating this augmented dynamic regression model by feasible generalized least squares using the long-run covariance matrix, we obtain an efficient estimator of the cointegrating vector that has a limiting mixed normal distribution. Simulation results suggest that this new estimator compares favorably with others already proposed in the literature. We apply these new estimators to the testing of purchasing power parity (PPP) among the G-7 countries. The test based on the efficient estimates rejects the PPP hypothesis for most countries.