963 resultados para Generalized Estimating Equations
Resumo:
An Enantiornithes specimen from El Montsec was initially described as an immature individual based upon qualitative traits such as its relatively large orbit and overall proportions of the skull and the postcranium. In this study we re-evaluate the precise determination of the ontogenetic stage of this individual, establishing a cross-talk among taphonomic, anatomic, and morphometric data. The exceptional preservation of the specimen has allowed pondering ontogenetic influence versus preservational bias in features like the external patterns of bone surfaces, instead of being aprioristically considered due to taphonomic alterations only. The rough texture of the periosteal bone associated with pores in the distal, proximal and mid-shaft areas of the humeral shaft, indicates a subadult stage when compared with long bones of modern birds. Forelimb proportions of embryo and juvenile Enanthiornithes are equivalent to those of adult individuals of other taxa within this clade, though this is not a reliable criterion for establishing a precise ontogenetic stage. The El Montsec specimen may be attributed a close adulthood, yet only if growth regimes in Enantiornithes are considered equivalent to those in Neornithes birds.
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Tutkimuksen tavoitteena oli rakentaa case yritykselle malli lyhyen aikavälin kannattavuuden estimointia varten. Tutkimusmetodi on konstruktiivinen, ja malli kehitettiin laskentaihmisten avustuksella. Teoriaosassa käytiin kirjallisuuskatsauksen avulla läpi kannattavuutta, budjetointia sekä itse ennustamista. Teoriaosassa pyrittiin löytämään sellaisia menetelmiä, joita voitaisiin käyttää lyhyen aikavälin kannattavuuden estimoinnissa. Rakennettavalle mallille asetettujen vaatimusten mukaan menetelmäksi valittiin harkintaan perustuva menetelmä (judgmental). Tutkimuksen mukaan kannattavuuteen vaikuttaa myyntihinta ja –määrä, tuotanto, raaka-aineiden hinnat ja varaston muutos. Rakennettu malli toimii kohdeyrityksessä kohtalaisen hyvin ja huomattavaa on se, että eri tehtaiden ja eri koneiden väliset erot saattavat olla kohtuullisen suuret. Nämä erot johtuvat pääasiassa tehtaan koosta ja mallien erilaisuudesta. Mallin käytännön toimivuus tulee kuitenkin parhaiten selville silloin, kun se on laskentaihmisten käytössä. Ennustamiseen liittyy kuitenkin aina omat ongelmansa ja uudetkaan menetelmät eivät välttämättä poista näitä ongelmia.
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The present study evaluates the performance of four methods for estimating regression coefficients used to make statistical decisions regarding intervention effectiveness in single-case designs. Ordinary least squares estimation is compared to two correction techniques dealing with general trend and one eliminating autocorrelation whenever it is present. Type I error rates and statistical power are studied for experimental conditions defined by the presence or absence of treatment effect (change in level or in slope), general trend, and serial dependence. The results show that empirical Type I error rates do not approximate the nominal ones in presence of autocorrelation or general trend when ordinary and generalized least squares are applied. The techniques controlling trend show lower false alarm rates, but prove to be insufficiently sensitive to existing treatment effects. Consequently, the use of the statistical significance of the regression coefficients for detecting treatment effects is not recommended for short data series.
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Past temperature variations are usually inferred from proxy data or estimated using general circulation models. Comparisons between climate estimations derived from proxy records and from model simulations help to better understand mechanisms driving climate variations, and also offer the possibility to identify deficiencies in both approaches. This paper presents regional temperature reconstructions based on tree-ring maximum density series in the Pyrenees, and compares them with the output of global simulations for this region and with regional climate model simulations conducted for the target region. An ensemble of 24 reconstructions of May-to-September regional mean temperature was derived from 22 maximum density tree-ring site chronologies distributed over the larger Pyrenees area. Four different tree-ring series standardization procedures were applied, combining two detrending methods: 300-yr spline and the regional curve standardization (RCS). Additionally, different methodological variants for the regional chronology were generated by using three different aggregation methods. Calibration verification trials were performed in split periods and using two methods: regression and a simple variance matching. The resulting set of temperature reconstructions was compared with climate simulations performed with global (ECHO-G) and regional (MM5) climate models. The 24 variants of May-to-September temperature reconstructions reveal a generally coherent pattern of inter-annual to multi-centennial temperature variations in the Pyrenees region for the last 750 yr. However, some reconstructions display a marked positive trend for the entire length of the reconstruction, pointing out that the application of the RCS method to a suboptimal set of samples may lead to unreliable results. Climate model simulations agree with the tree-ring based reconstructions at multi-decadal time scales, suggesting solar variability and volcanism as the main factors controlling preindustrial mean temperature variations in the Pyrenees. Nevertheless, the comparison also highlights differences with the reconstructions, mainly in the amplitude of past temperature variations and in the 20th century trends. Neither proxy-based reconstructions nor model simulations are able to perfectly track the temperature variations of the instrumental record, suggesting that both approximations still need further improvements.
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One of the most important problems in optical pattern recognition by correlation is the appearance of sidelobes in the correlation plane, which causes false alarms. We present a method that eliminate sidelobes of up to a given height if certain conditions are satisfied. The method can be applied to any generalized synthetic discriminant function filter and is capable of rejecting lateral peaks that are even higher than the central correlation. Satisfactory results were obtained in both computer simulations and optical implementation.
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We present the induced generalized ordered weighted averaging (IGOWA) operator. It is a new aggregation operator that generalizes the OWA operator by using the main characteristics of two well known aggregation operators: the generalized OWA and the induced OWA operator. Then, this operator uses generalized means and order inducing variables in the reordering process. With this formulation, we get a wide range of aggregation operators that include all the particular cases of the IOWA and the GOWA operator, and a lot of other cases such as the induced ordered weighted geometric (IOWG) operator and the induced ordered weighted quadratic averaging (IOWQA) operator. We further generalize the IGOWA operator by using quasi-arithmetic means. The result is the Quasi-IOWA operator. Finally, we also develop a numerical example of the new approach in a financial decision making problem.
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The 4πβ-γ coincidence counting method and its close relatives are widely used for the primary standardization of radioactivity. Both the general formalism and specific implementation of these methods have been well-documented. In particular, previous papers contain the extrapolation equations used for various decay schemes, methods for determining model parameters and, in some cases, tabulated uncertainty budgets. Two things often lacking from experimental reports are both the rationale for estimating uncertainties in a specific way and the details of exactly how a specific component of uncertainty was estimated. Furthermore, correlations among the components of uncertainty are rarely mentioned. To fill in these gaps, the present article shares the best-practices from a few practitioners of this craft. We explain and demonstrate with examples of how these approaches can be used to estimate the uncertainty of the reported massic activity. We describe uncertainties due to measurement variability, extrapolation functions, dead-time and resolving-time effects, gravimetric links, and nuclear and atomic data. Most importantly, a thorough understanding of the measurement system and its response to the decay under study can be used to derive a robust estimate of the measurement uncertainty.
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OBJECTIVE: To identify the clinical determinants of occurrence of postictal generalized EEG suppression (PGES) after generalized convulsive seizures (GCS). METHODS: We reviewed the video-EEG recordings of 417 patients included in the REPO2MSE study, a multicenter prospective cohort study of patients with drug-resistant focal epilepsy. According to ictal semiology, we classified GCS into 3 types: tonic-clonic GCS with bilateral and symmetric tonic arm extension (type 1), clonic GCS without tonic arm extension or flexion (type 2), and GCS with unilateral or asymmetric tonic arm extension or flexion (type 3). Association between PGES and person-specific or seizure-specific variables was analyzed after correction for individual effects and the varying number of seizures. RESULTS: A total of 99 GCS in 69 patients were included. Occurrence of PGES was independently associated with GCS type (p < 0.001) and lack of early administration of oxygen (p < 0.001). Odds ratio (OR) for GCS type 1 in comparison with GCS type 2 was 66.0 (95% confidence interval [CI 5.4-801.6]). In GCS type 1, risk of PGES was significantly increased when the seizure occurred during sleep (OR 5.0, 95% CI 1.2-20.9) and when oxygen was not administered early (OR 13.4, 95% CI 3.2-55.9). CONCLUSION: The risk of PGES dramatically varied as a function of GCS semiologic characteristics. Whatever the type of GCS, occurrence of PGES was prevented by early administration of oxygen.
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A BASIC computer program (REMOVAL) was developed to compute in a VAXNMS environment all the calculations of the removal method for population size estimation (catch-effort method for closed populations with constant sampling effort). The program follows the maximum likelihood methodology,checks the failure conditions, applies the appropriate formula, and displays the estimates of population size and catchability, with their standard deviations and coefficients of variation, and two goodness-of-fit statistics with their significance levels. Data of removal experiments for the cyprinodontid fish Aphanius iberus in the Alt Emporda wetlands are used to exemplify the use of the program
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We propose a new kernel estimation of the cumulative distribution function based on transformation and on bias reducing techniques. We derive the optimal bandwidth that minimises the asymptotic integrated mean squared error. The simulation results show that our proposed kernel estimation improves alternative approaches when the variable has an extreme value distribution with heavy tail and the sample size is small.