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Unknown Number (unknown + number)
Selected AbstractsLeast-squares Estimation of an Unknown Number of Shifts in a Time SeriesJOURNAL OF TIME SERIES ANALYSIS, Issue 1 2000Marc Lavielle In this contribution, general results on the off-line least-squares estimate of changes in the mean of a random process are presented. First, a generalisation of the Hajek-Renyi inequality, dealing with the fluctuations of the normalized partial sums, is given. This preliminary result is then used to derive the consistency and the rate of convergence of the change-points estimate, in the situation where the number of changes is known. Strong consistency is obtained under some mixing conditions. The limiting distribution is also computed under an invariance principle. The case where the number of changes is unknown is then addressed. All these results apply to a large class of dependent processes, including strongly mixing and also long-range dependent processes. [source] THE UNEMPLOYMENT PARADIGMS REVISITED: A COMPARATIVE ANALYSIS OF U.S. STATE AND EUROPEAN UNEMPLOYMENTCONTEMPORARY ECONOMIC POLICY, Issue 3 2009DIEGO ROMERO-ÁVILA This article tests the main unemployment paradigms for the unemployment rates of the states of the United States and the European Union,15 countries over the past three decades. For that purpose, we employ a state-of-the-art panel stationarity test, which allows for an unknown number of endogenous structural breaks as well as for cross-sectional correlation. Overall, our analysis renders clear-cut evidence in favor of regime-wise stationarity in U.S. state unemployment, while hysteresis in European unemployment. Interestingly, the timing of the breaks broadly coincides with major macroeconomic shocks mainly associated with the oil crises of the 1970s and marked changes in interest rates in the 1980s and early 1990s. Based on our results, we draw some policy prescriptions that point to the need for greater flexibility in the European labor markets. (JEL C23, E24) [source] A CENTENNIAL CELEBRATION FOR QUANTITATIVE GENETICSEVOLUTION, Issue 5 2007Derek A. Roff Quantitative genetics is at or is fast approaching its centennial. In this perspective I consider five current issues pertinent to the application of quantitative genetics to evolutionary theory. First, I discuss the utility of a quantitative genetic perspective in describing genetic variation at two very different levels of resolution, (1) in natural, free-ranging populations and (2) to describe variation at the level of DNA transcription. Whereas quantitative genetics can serve as a very useful descriptor of genetic variation, its greater usefulness is in predicting evolutionary change, particularly when used in the first instance (wild populations). Second, I review the contributions of Quantitative trait loci (QLT) analysis in determining the number of loci and distribution of their genetic effects, the possible importance of identifying specific genes, and the ability of the multivariate breeder's equation to predict the results of bivariate selection experiments. QLT analyses appear to indicate that genetic effects are skewed, that at least 20 loci are generally involved, with an unknown number of alleles, and that a few loci have major effects. However, epistatic effects are common, which means that such loci might not have population-wide major effects: this question waits upon (QTL) analyses conducted on more than a few inbred lines. Third, I examine the importance of research into the action of specific genes on traits. Although great progress has been made in identifying specific genes contributing to trait variation, the high level of gene interactions underlying quantitative traits makes it unlikely that in the near future we will have mechanistic models for such traits, or that these would have greater predictive power than quantitative genetic models. In the fourth section I present evidence that the results of bivariate selection experiments when selection is antagonistic to the genetic covariance are frequently not well predicted by the multivariate breeder's equation. Bivariate experiments that combine both selection and functional analyses are urgently needed. Finally, I discuss the importance of gaining more insight, both theoretical and empirical, on the evolution of the G and P matrices. [source] A polygenic heterogeneity model for common epilepsies with complex geneticsGENES, BRAIN AND BEHAVIOR, Issue 7 2007L. M. Dibbens Approximately 40% of epilepsy has a complex genetic basis with an unknown number of susceptibility genes. The effect of each susceptibility gene acting alone is insufficient to account for seizure phenotypes, but certain numbers or combinations of variations in susceptibility genes are predicted to raise the level of neuronal hyperexcitability above a seizure threshold for a given individual in a given environment. Identities of susceptibility genes are beginning to be determined, initially by translation of knowledge gained from gene discovery in the monogenic epilepsies. This entrée into idiopathic epilepsies with complex genetics has led to the experimental validation of susceptibility variants in the first few susceptibility genes. The genetic architecture so far emerging from these results is consistent with what we have designated as a polygenic heterogeneity model for the epilepsies with complex genetics. [source] Parameter estimation in selected populations with missing dataJOURNAL OF ANIMAL BREEDING AND GENETICS, Issue 2 2009G. Yagüe-Utrilla Summary This study proposes a procedure to estimate genetic parameters in populations where a selection process results in the loss of an unknown number of observations. The method was developed under the Bayesian inference scope following the missing data theory approach. Its implementation requires slight modifications to the Gibbs sampler algorithm. In order to show the efficiency of this option, a simulation study was conducted. [source] Hsp90: Chaperoning signal transductionJOURNAL OF CELLULAR PHYSIOLOGY, Issue 3 2001Klaus Richter Hsp90 is an ATP dependent molecular chaperone involved in the folding and activation of an unknown number of substrate proteins. These substrate proteins include protein kinases and transcription factors. Consistent with this task, Hsp90 is an essential protein in all eucaryotes. The interaction of Hsp90 with its substrate proteins involves the transient formation of multiprotein complexes with a set of highly conserved partner proteins. The specific function of each component in the processing of substrates is still unknown. Large ATP-dependent conformational changes of Hsp90 occur during the hydrolysis reaction and these changes are thought to drive the chaperone cycle. Natural inhibitors of the ATPase activity, like geldanamycin and radicicol, block the processing of Hsp90 substrate proteins. As many of these substrates are critical elements in signal transduction, Hsp90 seems to introduce an additional level of regulation. © 2001 Wiley-Liss, Inc. [source] Humoral immunity host factors in subjects with failing or successful titanium dental implantsJOURNAL OF CLINICAL PERIODONTOLOGY, Issue 12 2000Mats Kronström Abstract Background: Treatment with titanium dental implants is in general successful. However, an unknown number of implants do not integrate and are removed either by exfoliation or at the time of second stage surgery. It would be of importance to identify subjects at risk and predict early implant failure. Methods: In a retrospective study serum IgG antibody titers and avidity in sera from 40 subjects who had experienced titanium dental implant treatments with non-osseo-integration as the outcome (NOTI) and in sera from 40 age and gender matched control subjects who had received successful titanium dental implants (SOTI) were studied. Serum IgG titers to whole cell Actinomyces viscosus, Bacteroides forsythus, Porphyromonas gingivalis, Staphylococcus aureus, and Streptococcus intermedius sonicated antigen preparations were studied by ELISA. Results: Serum IgG antibody titers to S. aureus were significantly higher in subjects with SOTI than in NOTI (p<0.001) suggesting that higher titers indicate protection against implant failure as a result of S. aureus infection. Statistically significant higher serum IgG antibody avidity to P. gingivalis and B. forsythus were found in subjects with SOTI than in subjects with NOTI (p<0.01 and p<0.001, respectively). Statistical analysis failed to demonstrate antibody titer or avidity differences to the other pathogens studied. The likelihood that SOTI was associated with a high OD reading for S. aureus was 13.1:1 (p<0.001). Whether subjects were edentulous or not, or if they had lost teeth because of periodontitis or caries did not seem to matter. Conclusion: Serum IgG antibodies relative to B. forsythus, P. gingivalis and S. aureus may be associated with the outcome of implant procedures and explain why early implant failures occur. [source] Multi-component analysis: blind extraction of pure components mass spectra using sparse component analysisJOURNAL OF MASS SPECTROMETRY (INCORP BIOLOGICAL MASS SPECTROMETRY), Issue 9 2009Ivica Kopriva Abstract The paper presents sparse component analysis (SCA)-based blind decomposition of the mixtures of mass spectra into pure components, wherein the number of mixtures is less than number of pure components. Standard solutions of the related blind source separation (BSS) problem that are published in the open literature require the number of mixtures to be greater than or equal to the unknown number of pure components. Specifically, we have demonstrated experimentally the capability of the SCA to blindly extract five pure components mass spectra from two mixtures only. Two approaches to SCA are tested: the first one based on ,1 norm minimization implemented through linear programming and the second one implemented through multilayer hierarchical alternating least square nonnegative matrix factorization with sparseness constraints imposed on pure components spectra. In contrast to many existing blind decomposition methods no a priori information about the number of pure components is required. It is estimated from the mixtures using robust data clustering algorithm together with pure components concentration matrix. Proposed methodology can be implemented as a part of software packages used for the analysis of mass spectra and identification of chemical compounds. Copyright © 2009 John Wiley & Sons, Ltd. [source] Detection and correction of artificial shifts in climate seriesJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES C (APPLIED STATISTICS), Issue 3 2004Henri Caussinus Summary., Many long instrumental climate records are available and might provide useful information in climate research. These series are usually affected by artificial shifts, due to changes in the conditions of measurement and various kinds of spurious data. A comparison with surrounding weather-stations by means of a suitable two-factor model allows us to check the reliability of the series. An adapted penalized log-likelihood procedure is used to detect an unknown number of breaks and outliers. An example concerning temperature series from France confirms that a systematic comparison of the series together is valuable and allows us to correct the data even when no reliable series can be taken as a reference. [source] The determination of n -alkanes in the cuticular wax of leaves of Ludwigia adscendens L.PHYTOCHEMICAL ANALYSIS, Issue 2 2004A. Barik Abstract An n -hexane extract of fresh, mature leaves of Ludwigia adscendens, containing a thin layer of epicuticular waxes, has been analysed for the ,rst time by TLC, IR and GC using standard hydrocarbons. The leaves contained 22 identi,ed long chain (C15,C36) n -alkanes, accounting for 74.27% of the hydrocarbons present, and an unknown number of unidenti,ed branched chain alkanes. The predominant n -alkane was C25 (11.02%), whilst C18 (7.62%), C20 (6.14%), C29 (5.36%) and C27 (5.29%) n -alkanes were moderately abundant: the C35 homologue was present only in minor amounts (0.22%). Copyright © 2004 John Wiley & Sons, Ltd. [source] A fast distance-based approach for determining the number of components in mixturesTHE CANADIAN JOURNAL OF STATISTICS, Issue 1 2003Sujit K. Sahu Abstract The authors propose a procedure for determining the unknown number of components in mixtures by generalizing a Bayesian testing method proposed by Mengersen & Robert (1996). The testing criterion they propose involves a Kullback-Leibler distance, which may be weighted or not. They give explicit formulas for the weighted distance for a number of mixture distributions and propose a stepwise testing procedure to select the minimum number of components adequate for the data. Their procedure, which is implemented using the BUGS software, exploits a fast collapsing approach which accelerates the search for the minimum number of components by avoiding full refitting at each step. The performance of their method is compared, using both distances, to the Bayes factor approach. Les auteurs proposentune une façon de déterminer le nombre inconnu de composantes d'un mélange grâce à une généralisation d'un test bayésien de Mengersen & Robert (1996). Le critère qu'ils proposent repose sur une distance de Kullback-Leibler, laquelle peut être pondérée ou non. Ils calculent la distance pondérée explicitement pour divers mélanges de lois et proposent une procédure de test pas-à-pas conduisant au choix du plus petit nombre de composantes fournissant un bon ajustement. Leur procédure, implantée au moyen du logiciel BUGS, exploite la notion d'emboîtement pour accélérer les calculs nécessaires à ce choix en évitant qu'ils soient entièrement repris à chaque étape. La performance de leur technique est comparée à celle basée sur la notion de facteur de Bayes. [source] Post-release movements and habitat use of robust redhorse transplanted to the Ocmulgee River, Georgia,AQUATIC CONSERVATION: MARINE AND FRESHWATER ECOSYSTEMS, Issue 2 2009Timothy B. Grabowski Abstract 1.Robust redhorse Moxostoma robustum is an imperiled, potadromous fish in the south-eastern USA. Initial recovery efforts have focused on supplementing existing populations and establishing refugial populations through extensive stocking programmes. However, assessment of the success of these programmes has not yet been conducted, and there are few reports evaluating the effectiveness of such programmes with other potadromous species. 2.Radio telemetry was employed to assess the effectiveness of a stocking programme aimed at addressing whether stocked individuals would remain in an area free of introduced predators and ascertaining the ability of stocked fish to integrate into a resident population. 3.Hatchery-reared robust redhorse were captured from refugial populations established in other river systems and were transferred to the Ocmulgee River, Georgia where a population of hatchery-reared individuals and an unknown number of wild fish reside. 4.These transferred robust redhorse exhibited an exploratory phase for the first 3 months before adopting behaviour patterns, including spawning migrations, that were consistent with those reported for wild fish in other systems. However, some individuals seemed unable to locate suitable spawning habitat. 5.Approximately half of the radio-tagged fish remained within the area free of introduced predators. 6.At least some radio-tagged robust redhorse fully integrated into the resident population as evidenced by their presence in spawning aggregations with resident individuals. 7.The effectiveness of a stocking programme is dependent upon the ability of stocked individuals to integrate into an existing population or replicate the behaviour and functionality of a resident population. Evaluations of stocking programmes should incorporate assessments of behaviour in addition to surveys to estimate abundance and survivorship and genetic assessments of augmentation of effective population sizes. Published in 2008 by John Wiley & Sons, Ltd. [source] REVERSIBLE JUMP MARKOV CHAIN MONTE CARLO METHODS AND SEGMENTATION ALGORITHMS IN HIDDEN MARKOV MODELSAUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, Issue 2 2010R. Paroli Summary We consider hidden Markov models with an unknown number of regimes for the segmentation of the pixel intensities of digital images that consist of a small set of colours. New reversible jump Markov chain Monte Carlo algorithms to estimate both the dimension and the unknown parameters of the model are introduced. Parameters are updated by random walk Metropolis,Hastings moves, without updating the sequence of the hidden Markov chain. The segmentation (i.e. the estimation of the hidden regimes) is a further aim and is performed by means of a number of competing algorithms. We apply our Bayesian inference and segmentation tools to digital images, which are linearized through the Peano,Hilbert scan, and perform experiments and comparisons on both synthetic images and a real brain magnetic resonance image. [source] ESTIMATING COMPONENTS IN FINITE MIXTURES AND HIDDEN MARKOV MODELSAUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS, Issue 3 2005D.S. Poskitt Summary When the unobservable Markov chain in a hidden Markov model is stationary the marginal distribution of the observations is a finite mixture with the number of terms equal to the number of the states of the Markov chain. This suggests the number of states of the unobservable Markov chain can be estimated by determining the number of mixture components in the marginal distribution. This paper presents new methods for estimating the number of states in a hidden Markov model, and coincidentally the unknown number of components in a finite mixture, based on penalized quasi-likelihood and generalized quasi-likelihood ratio methods constructed from the marginal distribution. The procedures advocated are simple to calculate, and results obtained in empirical applications indicate that they are as effective as current available methods based on the full likelihood. Under fairly general regularity conditions, the methods proposed generate strongly consistent estimates of the unknown number of states or components. [source] Estimating the Species Accumulation Curve Using MixturesBIOMETRICS, Issue 2 2005Chang Xuan Mao Summary As a significant tool in ecological studies, the species accumulation curve or the collector's curve is the graph of the expected number of detected species as a function of sampling effort. The problem of estimating the species accumulation curve based on an empirical data set arising from quadrat sampling is studied in a nonparametric binomial mixture model. It will be shown that estimating the species accumulation curve not only is independent of the unknown number of species but also includes estimating the number of species as a limiting case. For the purpose of interpolation, moment-based estimators, associated with asymptotic confidence intervals, are developed from several points of view. A likelihood-based procedure is developed for the purpose of extrapolation, associated with bootstrap confidence intervals. The proposed methods are illustrated by ecological data sets. [source] | |||||||||||||||||||