972 resultados para Maximum entropy statistical estimate


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This paper seeks to identify whether there is a representative empirical Okun’s Law coefficient (OLC) and to measure its size. We carry out a meta regression analysis on a sample of 269 estimates of the OLC to uncover reasons for differences in empirical results and to estimate the ‘true’ OLC. On statistical (and other) grounds, we find it appropriate to investigate two separate subsamples, using respectively (some measure of) unemployment or output as dependent variable. Our results can be summarized as follows. First, there is evidence of type II publication bias in both sub-samples, but a type I bias is present only among the papers using some measure of unemployment as the dependent variable. Second, after correction for publication bias, authentic and statistically significant OLC effects are present in both sub-samples. Third, bias-corrected estimated true OLCs are significantly lower (in absolute value) with models using some measure of unemployment as the dependent variable. Using a bivariate MRA approach, the estimated true effects are -0.25 for the unemployment sub-sample and -0.61 for the output-sub sample; with a multivariate MRA methodology, the estimated true effects are -0.40 and -1.02 for the unemployment and the output-sub samples respectively.

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Time-lapse crosshole ground-penetrating radar (GPR) data, collected while infiltration occurs, can provide valuable information regarding the hydraulic properties of the unsaturated zone. In particular, the stochastic inversion of such data provides estimates of parameter uncertainties, which are necessary for hydrological prediction and decision making. Here, we investigate the effect of different infiltration conditions on the stochastic inversion of time-lapse, zero-offset-profile, GPR data. Inversions are performed using a Bayesian Markov-chain-Monte-Carlo methodology. Our results clearly indicate that considering data collected during a forced infiltration test helps to better refine soil hydraulic properties compared to data collected under natural infiltration conditions

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This paper develops a methodology to estimate the entire population distributions from bin-aggregated sample data. We do this through the estimation of the parameters of mixtures of distributions that allow for maximal parametric flexibility. The statistical approach we develop enables comparisons of the full distributions of height data from potential army conscripts across France's 88 departments for most of the nineteenth century. These comparisons are made by testing for differences-of-means stochastic dominance. Corrections for possible measurement errors are also devised by taking advantage of the richness of the data sets. Our methodology is of interest to researchers working on historical as well as contemporary bin-aggregated or histogram-type data, something that is still widely done since much of the information that is publicly available is in that form, often due to restrictions due to political sensitivity and/or confidentiality concerns.

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'Modern' theories of the Phillips curve imply that inflation is an integrated, or near integrated process. This paper explains this implication and why these 'modern' theories are logically inconsistent with what is commonly known about the statistical process of inflation.

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I construct "homogeneous" series of GVA at current and constant prices, employment and population for the Spain and its regions covering the period 1955-2007. The series are obtained by linking the Regional Accounts of the National Statistical Institute with the series constructed by Julio Alcaide and his team for the BBVA Foundation. The "switching point" at which this last source stops being used as a reference to construct the linked series is determined using a procedure that allows me to estimate which of the two competing series would produce an estimator with the lowest MSE when it is used as dependent variable in a regression on an arbitrary independent variable. To the extent that it is possible, the difference between the two series found at the point of linkage is distributed between the initial levels of the older series and its subsequent growth using external estimates of the relevant variables at the beginning of the sample period.

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We propose a mixed finite element method for a class of nonlinear diffusion equations, which is based on their interpretation as gradient flows in optimal transportation metrics. We introduce an appropriate linearization of the optimal transport problem, which leads to a mixed symmetric formulation. This formulation preserves the maximum principle in case of the semi-discrete scheme as well as the fully discrete scheme for a certain class of problems. In addition solutions of the mixed formulation maintain exponential convergence in the relative entropy towards the steady state in case of a nonlinear Fokker-Planck equation with uniformly convex potential. We demonstrate the behavior of the proposed scheme with 2D simulations of the porous medium equations and blow-up questions in the Patlak-Keller-Segel model.

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The usual way to investigate the statistical properties of finitely generated subgroups of free groups, and of finite presentations of groups, is based on the so-called word-based distribution: subgroups are generated (finite presentations are determined) by randomly chosen k-tuples of reduced words, whose maximal length is allowed to tend to infinity. In this paper we adopt a different, though equally natural point of view: we investigate the statistical properties of the same objects, but with respect to the so-called graph-based distribution, recently introduced by Bassino, Nicaud and Weil. Here, subgroups (and finite presentations) are determined by randomly chosen Stallings graphs whose number of vertices tends to infinity. Our results show that these two distributions behave quite differently from each other, shedding a new light on which properties of finitely generated subgroups can be considered frequent or rare. For example, we show that malnormal subgroups of a free group are negligible in the raph-based distribution, while they are exponentially generic in the word-based distribution. Quite surprisingly, a random finite presentation generically presents the trivial group in this new distribution, while in the classical one it is known to generically present an infinite hyperbolic group.

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Limited information is available regarding the methodology required to characterize hashish seizures for assessing the presence or the absence of a chemical link between two seizures. This casework report presents the methodology applied for assessing that two different police seizures were coming from the same block before this latter one was split. The chemical signature was extracted using GC-MS analysis and the implemented methodology consists in a study of intra- and inter-variability distributions based on the measurement of the chemical profiles similarity using a number of hashish seizures and the calculation of the Pearson correlation coefficient. Different statistical scenarios (i.e., a combination of data pretreatment techniques and selection of target compounds) were tested to find the most discriminating one. Seven compounds showing high discrimination capabilities were selected on which a specific statistical data pretreatment was applied. Based on the results, the statistical model built for comparing the hashish seizures leads to low error rates. Therefore, the implemented methodology is suitable for the chemical profiling of hashish seizures.

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OBJECTIVES: Family studies typically use multiple sources of information on each individual including direct interviews and family history information. The aims of the present study were to: (1) assess agreement for diagnoses of specific substance use disorders between direct interviews and the family history method; (2) compare prevalence estimates according to the two methods; (3) test strategies to approximate prevalence estimates according to family history reports to those based on direct interviews; (4) determine covariates of inter-informant agreement; and (5) identify covariates that affect the likelihood of reporting disorders by informants. METHODS: Analyses were based on family study data which included 1621 distinct informant (first-degree relatives and spouses) - index subject pairs. RESULTS: Our main findings were: (1) inter-informant agreement was fair to good for all substance disorders, except for alcohol abuse; (2) the family history method underestimated the prevalence of drug but not alcohol use disorders; (3) lowering diagnostic thresholds for drug disorders and combining multiple family histories increased the accuracy of prevalence estimates for these disorders according to the family history method; (4) female sex of index subjects was associated with higher agreement for nearly all disorders; and (5) informants who themselves had a history of the same substance use disorder were more likely to report this disorder in their relatives, which entails the risk of overestimation of the size of familial aggregation. CONCLUSION: Our findings have important implications for the best-estimate procedure applied in family studies.

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OBJECTIVES: The aim of the study was to assess whether prospective follow-up data within the Swiss HIV Cohort Study can be used to predict patients who stop smoking; or among smokers who stop, those who start smoking again. METHODS: We built prediction models first using clinical reasoning ('clinical models') and then by selecting from numerous candidate predictors using advanced statistical methods ('statistical models'). Our clinical models were based on literature that suggests that motivation drives smoking cessation, while dependence drives relapse in those attempting to stop. Our statistical models were based on automatic variable selection using additive logistic regression with component-wise gradient boosting. RESULTS: Of 4833 smokers, 26% stopped smoking, at least temporarily; because among those who stopped, 48% started smoking again. The predictive performance of our clinical and statistical models was modest. A basic clinical model for cessation, with patients classified into three motivational groups, was nearly as discriminatory as a constrained statistical model with just the most important predictors (the ratio of nonsmoking visits to total visits, alcohol or drug dependence, psychiatric comorbidities, recent hospitalization and age). A basic clinical model for relapse, based on the maximum number of cigarettes per day prior to stopping, was not as discriminatory as a constrained statistical model with just the ratio of nonsmoking visits to total visits. CONCLUSIONS: Predicting smoking cessation and relapse is difficult, so that simple models are nearly as discriminatory as complex ones. Patients with a history of attempting to stop and those known to have stopped recently are the best candidates for an intervention.

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We aimed to determine whether human subjects' reliance on different sources of spatial information encoded in different frames of reference (i.e., egocentric versus allocentric) affects their performance, decision time and memory capacity in a short-term spatial memory task performed in the real world. Subjects were asked to play the Memory game (a.k.a. the Concentration game) without an opponent, in four different conditions that controlled for the subjects' reliance on egocentric and/or allocentric frames of reference for the elaboration of a spatial representation of the image locations enabling maximal efficiency. We report experimental data from young adult men and women, and describe a mathematical model to estimate human short-term spatial memory capacity. We found that short-term spatial memory capacity was greatest when an egocentric spatial frame of reference enabled subjects to encode and remember the image locations. However, when egocentric information was not reliable, short-term spatial memory capacity was greater and decision time shorter when an allocentric representation of the image locations with respect to distant objects in the surrounding environment was available, as compared to when only a spatial representation encoding the relationships between the individual images, independent of the surrounding environment, was available. Our findings thus further demonstrate that changes in viewpoint produced by the movement of images placed in front of a stationary subject is not equivalent to the movement of the subject around stationary images. We discuss possible limitations of classical neuropsychological and virtual reality experiments of spatial memory, which typically restrict the sensory information normally available to human subjects in the real world.

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A sound statistical methodology is presented for modelling the correspondence between the characteristics of individuals, their thermal environment, and their thermal sensation. The proposed methodology substantially improves that developed by P.O. Fanger, by formulating a more general and precise model of thermal comfort. It enables us to estimate the model from a sample of data where all the parameters of comfort vary at the same time, which is not possible with that adopted by Fanger. Moreover, the present model is still valid when thermal conditions are far from optimum. (C) 1997 Elsevier Science Ltd.

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A gradual increase in Earth's surface temperatures marking the transition from the late Paleocene to early Eocene (55.8±0.2Ma), represents an extraordinary warming event known as Paleocene-Eocene Thermal Maximum (PETM). Both marine and continental sedimentary records during this period reveal evidences for the massive injection of isotopically light carbon. The carbon dioxide injection from multiple potential sources may have triggered the global warming. The importance of the PETM studies is due to the fact that the PETM bears some striking resemblances to the human-caused climate change unfolding today. Most notably, the culprit behind it was a massive injection of heat-trapping greenhouse gases into the atmosphere and oceans, comparable in volume to what our persistent burning of fossil fuels could deliver in coming centuries. The exact knowledge of what went on during the PETM could help us to foresee the future climate change. The response of the oceanic and continental environments to the PETM is different. Many factors might control the response of the environments to the PETM such as paleogeography, paleotopography, paleoenvironment, and paleodepth. To better understand the mechanisms triggering PETM events, two different environments were studied: 1) shallow marine to inner shelf environment (Wadi Nukhul, Sinai; and the Dababiya GSSP, Luxor, Egypt), and 2) terrestrial environments (northwestern India lignite mines) representing wetland, and fluvial environments (Esplugafreda, Spain) both highlighting the climatic changes observed in continental conditions. In the marine realm, the PETM is characterized by negative ö13Ccar and ô13Corg excursions and shifts in Ô15N to ~0%o values above the P/E boundary and persisting along the interval suggesting a bloom and high production of atmospheric N2-fixers. Decrease in carbonate contents could be due to dissolution and/or dilution by increasing detrital input. High Ti, K and Zr and decreased Si contents at the P/E boundary indicate high weathering index (CIA), which coincides with significant kaolinite input and suggests intense chemical weathering under humid conditions at the beginning of the PETM. Two anoxic intervals are observed along the PETM. The lower one may be linked to methane released from the continental shelf with no change in the redox proxies, where the upper anoxic to euxinic conditions are revealed by increasing U, Mo, V, Fe and the presence of small size pyrite framboids (2-5fim). Productivity sensitive elements (Cu, Ni, and Cd) show their maximum concentrated within the upper anoxic interval suggesting high productivity in surface water. The obtained data highlight that intense weathering and subsequent nutrient inputs are crucial parameters in the chain of the PETM events, triggering productivity during the recovery phase. In the terrestrial environments, the establishment of wetland conditions and consequence continental climatic shift towards more humid conditions led to migration of modern mammals northward following the extension of the tropical belts. Relative ages of this mammal event based on bio-chemo- and paleomagnetic stratigraphy support a migration path originating from Asia into Europe and North America, followed by later migration from Asia into India and suggests a barrier to migration that is likely linked to the timing of the India-Asia collision. In contrast, at Esplugafereda, northeastern Spain, the terrestrial environment reacted differently. Two significant S13C shifts with the lower one linked to the PETM and the upper corresponding to the Early Eocene Thermal Maximum (ETM2); 180/160 paleothermometry performed on two different soil carbonate nodule reveal a temperature increase of around 8°C during the PETM. The prominent increase in kaolinite content within the PETM is linked to increased runoff and/or weathering of adjacent and coeval soils. These results demonstrate that the PETM coincides globally with extreme climatic fluctuations and that terrestrial environments are very likely to record such climatic changes. - La transition Paléocène-Eocène (55,8±0,2 Ma) est marquée par un réchauffement extraordinaire communément appelé « Paleocene-Eocene Thermal Maximum » (PETM). Les données géochimiques caractérisant les sédiments marins et continentaux de cette période indiquent que ce réchauffement a été déclenché par une augmentation massive de CO2 lié à la déstabilisation des hydrates de méthane stockés le long des marges océaniques. L'étude des événements PETM constitue donc un bon analogue avec le réchauffement actuel. Le volume de CO2 émis durant le PETM est comparable avec le CO2 lié à l'activité actuelle humaine. La compréhension des causes du réchauffement du PETM peut être cruciale pour prévoir et évaluer les conséquences du réchauffement anthropogénique, en particulier les répercussions d'un tel réchauffement sur les domaines continentaux et océaniques. De nombreux facteurs entrent en ligne de compte dans le cas du PETM, tels que la paléogéographie, la paléotopographie et les paléoenvironnement. Pour mieux comprendre les réponses environnementales aux événements du PETM, 2 types d'environnements ont été choisis : (1) le domaine marin ouvert mais relativement peu profond (Wadi Nukhul. Sinai, Dababiya, Luxor, Egypte), (2) le milieu continental marécageux humide (mines de lignite, Inde) et fluviatile, semi-aride (Esplugafreda, Pyrénées espagnoles). Dans le domaine marin, le PETM est caractérisé par des excursions négatives du ô13Ccar et ô13Corg et un shift persistant des valeurs de 815N à ~ 0 %o indiquant une forte activité des organismes (bactéries) fixant l'azote. La diminution des carbonates observée durant le PETM peut-être due à des phénomènes de dissolution ou une augmentation des apports terrigènes. Des taux élevés en Ti, K et Zr et une diminution des montants de Si, reflétés par des valeurs des indices d'altération (CIA) qui coïncident avec une augmentation significative des apports de kaolinite impliquent une altération chimique accrue, du fait de conditions plus humides au début du PETM. Deux événements anoxiques globaux ont été mis en évidence durant le PETM. Le premier, situé dans la partie inférieur du PETM, serait lié à la libération des hydrates de méthane stockés le long des talus continentaux et ne correspond pas à des variations significatives des éléments sensibles aux changements de conditions redox. Le second est caractérisé par une augmentation des éléments U, Mo, V et Fe et la présence de petit framboids de pyrite dont la taille varie entre 2 et 5pm. Le second épisode anoxique est caractérisé par une forte augmentation des éléments sensibles aux changements de la productivité (Cu, Ni et Co), indiquant une augmentation de la productivité dans les eaux de surface. Les données obtenues mettent en évidence le rôle crucial joué par l'altération et les apports en nutriments qui en découlent. Ces paramètres sont cruciaux pour la succession des événements qui ont conduit au PETM, et plus particulièrement l'augmentation de la productivité dans la phase de récupération. Durant le PETM, le milieu continental est caractérisé par l'établissement de conditions humides qui ont facilité voir provoqué la migration des mammifères modernes qui ont suivi le déplacement de ces ceintures climatiques. L'âge de cette migration est basé sur des arguments chimiostratigraphiques (isotopes stables), biostratigraphiques et paléomagnétiques. Les données bibliographiques ainsi que celles que nous avons récoltées en Inde, montrent que les mammifères modernes ont d'abord migré depuis l'Asie vers l'Europe, puis dans le continent Nord américain. Ces derniers ne sont arrivés en Inde que plus tardivement, suggérant que le temps de leur migration est lié à la collision Inde-Asie. Dans le Nord-Est de l'Espagne (Esplugafreda), la réponse du milieu continental aux événements PETM est assez différente. Comme en Inde, deux excursions signicatives en ô13C ont été observées. La première correspond au PETM et la seconde est corrélée avec l'optimum thermique de l'Eocène précoce (ETM2). Les isotopes stables de l'oxygène mesurés 2 différents types de nodules calcaires provenant de paléosols suggère une augmentation de 10°C pendant le PETM. Une augmentation simultanée des taux de kaolinite indique une intensification de l'altération chimique et/ou de l'érosion de sols adjacents. Ces résultats démontrent que le PETM coïncide globalement avec des variations climatiques extrêmes qui sont très aisément reconnaissables dans les dépôts continentaux.

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Empirical modeling of exposure levels has been popular for identifying exposure determinants in occupational hygiene. Traditional data-driven methods used to choose a model on which to base inferences have typically not accounted for the uncertainty linked to the process of selecting the final model. Several new approaches propose making statistical inferences from a set of plausible models rather than from a single model regarded as 'best'. This paper introduces the multimodel averaging approach described in the monograph by Burnham and Anderson. In their approach, a set of plausible models are defined a priori by taking into account the sample size and previous knowledge of variables influent on exposure levels. The Akaike information criterion is then calculated to evaluate the relative support of the data for each model, expressed as Akaike weight, to be interpreted as the probability of the model being the best approximating model given the model set. The model weights can then be used to rank models, quantify the evidence favoring one over another, perform multimodel prediction, estimate the relative influence of the potential predictors and estimate multimodel-averaged effects of determinants. The whole approach is illustrated with the analysis of a data set of 1500 volatile organic compound exposure levels collected by the Institute for work and health (Lausanne, Switzerland) over 20 years, each concentration having been divided by the relevant Swiss occupational exposure limit and log-transformed before analysis. Multimodel inference represents a promising procedure for modeling exposure levels that incorporates the notion that several models can be supported by the data and permits to evaluate to a certain extent model selection uncertainty, which is seldom mentioned in current practice.