918 resultados para dynamic factor models


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Background: The Strengths and Difficulties Questionnaire (SDQ) is a tool to measure the risk for mental disorders in children. The aim of this study is to describe the diagnostic efficiency and internal structure of the SDQ in the sample of children studied in the Spanish National Health Survey 2006. Methods: A representative sample of 6,773 children aged 4 to 15 years was studied. The data were obtained using the Minors Questionnaire in the Spanish National Health Survey 2006. The ROC curve was constructed and calculations made of the area under the curve, sensitivity, specificity and the Youden J indices. The factorial structure was studied using models of exploratory factorial analysis (EFA) and confirmatory factorial analysis (CFA). Results: The prevalence of behavioural disorders varied between 0.47% and 1.18% according to the requisites of the diagnostic definition. The area under the ROC curve varied from 0.84 to 0.91 according to the diagnosis. Factor models were cross-validated by means of two different random subsamples for EFA and CFA. An EFA suggested a three correlated factor model. CFA confirmed this model. A five-factor model according to EFA and the theoretical five-factor model described in the bibliography were also confirmed. The reliabilities of the factors of the different models were acceptable (>0.70, except for one factor with reliability 0.62). Conclusions: The diagnostic behaviour of the SDQ in the Spanish population is within the working limits described in other countries. According to the results obtained in this study, the diagnostic efficiency of the questionnaire is adequate to identify probable cases of psychiatric disorders in low prevalence populations. Regarding the factorial structure we found that both the five and the three factor models fit the data with acceptable goodness of fit indexes, the latter including an externalization and internalization dimension and perhaps a meaningful positive social dimension. Accordingly, we recommend studying whether these differences depend on sociocultural factors or are, in fact, due to methodological questions.

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This paper develops a new underlying inflation gauge (UIG) for China which differentiates between trend and noise, is available daily and uses a broad set of variables that potentially influence inflation. Its construction follows the works at other major central banks, adopts the methodology of a dynamic factor model that extracts the lower frequency components as developed by Forni et al (2000) and draws on the experience of the People’s Bank of China in modelling inflation.

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Ordered mesoporous materials show great importance in energy, environmental, and chemical engineering. The diffusion of guest species in mesoporous networks plays an important role in these applications, especially for energy storage, such as supercapacitors based on ordered mesoporous carbons ( OMCs). The ion diffusion behavior in two different 2-D hexagonal OMCs was investigated by using cyclic voltametry and electrochemical impedance spectroscopy. In addition, transmission electron microscopy, small-angle X-ray diffraction, and nitrogen cryosorption methods were used to study the pore structure variations of these two OMCs. It was found that, for the OMC with defective pore channels ( termed as pore packing defects), the gravimetric capacitance was greatly decayed when the voltage scan rate was increased. The experimental results suggest that, for the ion diffusion in 2-D hexagonal OMCs with similar mesopore size distribution, the pore packing defect is a dominant dynamic factor.

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Background The Hospital Anxiety and Depression Scale (HADS) is a widely used screening tool designed as a case detector for clinically relevant anxiety and depression. Recent studies of the HADS in coronary heart disease (CHD) patients in European countries suggest it comprises three, rather than two, underlying sub-scale dimensions. The factor structure of the Chinese version of the HADS was evaluated in patients with CHD in mainland China. Methods Confirmatory factor analysis (CFA) was conducted on self-report HADS forms from 154 Chinese CHD patients. Results Little difference was observed in model fit between best performing three-factor and two-factor models. Conclusion The current observations are inconsistent with recent studies highlighting a dominant underlying tri-dimensional structure to the HADS in CHD patients. The Chinese version of the HADS may perform differently to European language versions of the instrument in patients with CHD.

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The investigation of insulation debris generation, transport and sedimentation becomes more important with regard to reactor safety research for pressurized and boiling water reactors, when considering the long-term behaviour of emergency core coolant systems during all types of loss of coolant accidents (LOCA). The insulation debris released near the break during a LOCA incident consists of a mixture of a disparate particle population that varies with size, shape, consistency and other properties. Some fractions of the released insulation debris can be transported into the reactor sump, where it may perturb or impinge on the emergency core cooling systems. Open questions of generic interest are for example the particle load on strainers and corresponding pressure-drop, the sedimentation of the insulation debris in a water pool, its possible re-suspension and transport in the sump water flow. A joint research project on such questions is being performed in cooperation with the University of Applied Science Zittau/Görlitz and the Forschungszentrum Dresden-Rossendorf. The project deals with the experimental investigation and the development of computational fluid dynamic (CFD) models for the description of particle transport phenomena in coolant flow. While the experiments are performed at the University Zittau/Görlitz, the theoretical work is concentrated at Forschungszentrum Dresden-Rossendorf. In the present paper, the basic concepts for computational fluid dynamic (CFD) modelling are described and experimental results are presented. Further experiments are designed and feasibility studies were performed.

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This study analyzes the validity of different Q-factor models in the BER estimation in RZ-DPSK transmission at 40 Gb/s channel rate. The impact of the duty cycle of the carrier pulses on the accuracy of the BER estimates through the different models has also been studied.

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This study examines the relationship between executive directors’ remuneration and the financial performance and corporate governance arrangements of the UK and Spanish listed firms. These countries’ corporate governance framework has been shaped by differences in legal origin, culture and backgrounds. For example, the UK legal arrangements can be defined as to be constituted in common-law, whereas for Spanish firms, the legal arrangement is based on civil law. We estimate both static and dynamic regression models to test our hypotheses and we estimate our regression using Ordinary Least Squares (OLS) and the Generalised Method of Moments (GMM). Estimated results for both countries show that directors’ remuneration levels are positively related with measures of firm value and financial performance. This means that remuneration levels do not lead to a point whereby firm value is reduced due to excessive remuneration. These results hold for our long-run estimates. That is, estimates based on panel cointegration and panel error correction. Measures of corporate governance also impacts on the level of executive pay. Our results have important implications for existing corporate governance arrangements and how the interests of stakeholders are protected. For example, long-run results suggest that directors’ remuneration adjusts in a way to capture variation in financial performance

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This study analyzes the validity of different Q-factor models in the BER estimation in RZ-DPSK transmission at 40 Gb/s channel rate. The impact of the duty cycle of the carrier pulses on the accuracy of the BER estimates through the different models has also been studied.

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Climate change has a great impact on the build and the work of natural ecosystems. Disappearance of some population or growth of the number in some species can be already caused by little change in temperature. A Theoretical Ecosystem Growth Model was investigated in order to examine the effects of various climate patterns on the ecological equilibrium. The answers of the ecosystems which are given to the climate change could be described by means of global climate modelling and dynamic vegetation models. The examination of the operation of the ecosystems is only possible in huge centres on supercomputers because of the number and the complexity of the calculation. The number of the calculation could be decreased to the level of a PC by considering the temperature and the reproduction during the modelling of a theoretical ecosystem and several important theoretical questions could be answered.

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Climate change has serious effects on the setting up and the operation of natural ecosystems. Small increase in temperature could cause rise in the amount of some species or potential disappearance of others. During our researches, the dispersion of the species and biomass production of a theoretical ecosystem were examined on the effect of the temperature–climate change. The answers of the ecosystems which are given to the climate change could be described by means of global climate modelling and dynamic vegetation models. The examination of the operation of the ecosystems is only possible in huge centres on supercomputers because of the number and the complexity of the calculation. The number of the calculation could be decreased to the level of a PC by considering the temperature and the reproduction during modelling a theoretical ecosystem, and several important theoretical questions could be answered.

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The purpose of the present dissertation was to evaluate the internal validity of symptoms of four common anxiety disorders included in the Diagnostic and Statistical Manual of Mental Disorders fourth edition (text revision) (DSM-IV-TR; American Psychiatric Association, 2000), namely, separation anxiety disorder (SAD), social phobia (SOP), specific phobia (SP), and generalized anxiety disorder (GAD), in a sample of 625 youth (ages 6 to 17 years) referred to an anxiety disorders clinic and 479 parents. Confirmatory factor analyses (CFAs) were conducted on the dichotomous items of the SAD, SOP, SP, and GAD sections of the youth and parent versions of the Anxiety Disorders Interview Schedule for DSM-IV (ADIS-IV: C/P; Silverman & Albano, 1996) to test and compare a number of factor models including a factor model based on the DSM. Contrary to predictions, findings from CFAs showed that a correlated model with five factors of SAD, SOP, SP, GAD worry, and GAD somatic distress, provided the best fit of the youth data as well as the parent data. Multiple group CFAs supported the metric invariance of the correlated five factor model across boys and girls. Thus, the present study’s finding supports the internal validity of DSM-IV SAD, SOP, and SP, but raises doubt regarding the internal validity of GAD.^

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Globalization and technological changes that has happened since the 80s have brought remarkable changes in the industrial and commercial paradigm, which are expressed mainly in the international fragmentation of production and in the formation of Global Value Chains (GVC). This thesis sought to understand such phenomena and discuss new relevant variables in this context for a more accurate analysis of the current trade patterns not addressed by the seminal economic theories that relate trade and economic growth. It sought to evaluate how the trade specialization pattern of Brazil evolved compared to other economies (China, India, Russia, United States, Japan and selected Latin American economies) in the light of these phenomena from 1995 to 2011. Therefore, we have used the methodology of gross exports decomposition in value added measures, developed by Koopman et al. (2014), and indicators estimated from data of two global matrices I-O: a WIOT (2013) and the TiVA (2015). It was also tested two hypotheses regarding the role of these phenomena as determinants of economic growth in recent years: 1º) fragmentation and participation in GVC ensure higher growth rates for countries; 2º) the place (stage) in which the country finds itself in GVC associated with sectoral technological aspects is also important for economic growth. For this, we used dynamic panel models (Difference GMM and System GMM) for a sample of 40 countries from 2003 to 2011. The studies carried out on Brazil show that the country is no longer on the margins of these phenomena, because it shows increasing rates of participation in GVC, including in sectors considered most strategic for fragmentation. However, there is not a standard convergence of trade specialization of the country to those presented by developed countries or movements earned by China and Mexico in terms of their position and profile of participating in GVC. Another important result obtained by the thesis is the identification of these phenomena are in fact new variables relevant for economic growth, because it shows empirical evidences to support the hypothesis 1 and, partially, the hypothesis 2. A joint analysis of the estimated econometric results with the results of the descriptive analysis of the Brazilian economy, it leads us to conclude that the trade specialization pattern of the country in the context of the new trade setups is presented unfavorably to its growth strategy.

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The advances in three related areas of state-space modeling, sequential Bayesian learning, and decision analysis are addressed, with the statistical challenges of scalability and associated dynamic sparsity. The key theme that ties the three areas is Bayesian model emulation: solving challenging analysis/computational problems using creative model emulators. This idea defines theoretical and applied advances in non-linear, non-Gaussian state-space modeling, dynamic sparsity, decision analysis and statistical computation, across linked contexts of multivariate time series and dynamic networks studies. Examples and applications in financial time series and portfolio analysis, macroeconomics and internet studies from computational advertising demonstrate the utility of the core methodological innovations.

Chapter 1 summarizes the three areas/problems and the key idea of emulating in those areas. Chapter 2 discusses the sequential analysis of latent threshold models with use of emulating models that allows for analytical filtering to enhance the efficiency of posterior sampling. Chapter 3 examines the emulator model in decision analysis, or the synthetic model, that is equivalent to the loss function in the original minimization problem, and shows its performance in the context of sequential portfolio optimization. Chapter 4 describes the method for modeling the steaming data of counts observed on a large network that relies on emulating the whole, dependent network model by independent, conjugate sub-models customized to each set of flow. Chapter 5 reviews those advances and makes the concluding remarks.

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Paleotopographic models of the West Antarctic margin, which are essential for robust simulations of paleoclimate scenarios, lack information on sediment thickness and geodynamic conditions, resulting in large uncertainties. A new total sediment thickness grid spanning the Ross Sea-Amundsen Sea-Bellingshausen Sea basins is presented and is based on all the available seismic reflection, borehole, and gravity modeling data offshore West Antarctica. This grid was combined with NGDC's global 5 arc minute grid of ocean sediment thickness (Whittaker et al., 2013, doi:10.1002/ggge.20181) and extends the NGDC grid further to the south. Sediment thickness along the West Antarctic margin tends to be 3-4 km larger than previously assumed. The sediment volume in the Bellingshausen, Amundsen, and Ross Sea basins amounts to 3.61, 3.58, and 2.78 million km³, respectively. The residual basement topography of the South Pacific has been revised and the new data show an asymmetric trend over the Pacific-Antarctic Ridge. Values are anomalously high south of the spreading ridge and in the Ross Sea area, where the topography seems to be affected by persistent mantle processes. In contrast, the basement topography offshore Marie Byrd Land cannot be attributed to dynamic topography, but rather to crustal thickening due to intraplate volcanism. Present-day dynamic topography models disagree with the presented revised basement topography of the South Pacific, rendering paleotopographic reconstructions with such a limited dataset still fairly uncertain.

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Cette thèse développe des méthodes bootstrap pour les modèles à facteurs qui sont couram- ment utilisés pour générer des prévisions depuis l'article pionnier de Stock et Watson (2002) sur les indices de diffusion. Ces modèles tolèrent l'inclusion d'un grand nombre de variables macroéconomiques et financières comme prédicteurs, une caractéristique utile pour inclure di- verses informations disponibles aux agents économiques. Ma thèse propose donc des outils éco- nométriques qui améliorent l'inférence dans les modèles à facteurs utilisant des facteurs latents extraits d'un large panel de prédicteurs observés. Il est subdivisé en trois chapitres complémen- taires dont les deux premiers en collaboration avec Sílvia Gonçalves et Benoit Perron. Dans le premier article, nous étudions comment les méthodes bootstrap peuvent être utilisées pour faire de l'inférence dans les modèles de prévision pour un horizon de h périodes dans le futur. Pour ce faire, il examine l'inférence bootstrap dans un contexte de régression augmentée de facteurs où les erreurs pourraient être autocorrélées. Il généralise les résultats de Gonçalves et Perron (2014) et propose puis justifie deux approches basées sur les résidus : le block wild bootstrap et le dependent wild bootstrap. Nos simulations montrent une amélioration des taux de couverture des intervalles de confiance des coefficients estimés en utilisant ces approches comparativement à la théorie asymptotique et au wild bootstrap en présence de corrélation sérielle dans les erreurs de régression. Le deuxième chapitre propose des méthodes bootstrap pour la construction des intervalles de prévision permettant de relâcher l'hypothèse de normalité des innovations. Nous y propo- sons des intervalles de prédiction bootstrap pour une observation h périodes dans le futur et sa moyenne conditionnelle. Nous supposons que ces prévisions sont faites en utilisant un ensemble de facteurs extraits d'un large panel de variables. Parce que nous traitons ces facteurs comme latents, nos prévisions dépendent à la fois des facteurs estimés et les coefficients de régres- sion estimés. Sous des conditions de régularité, Bai et Ng (2006) ont proposé la construction d'intervalles asymptotiques sous l'hypothèse de Gaussianité des innovations. Le bootstrap nous permet de relâcher cette hypothèse et de construire des intervalles de prédiction valides sous des hypothèses plus générales. En outre, même en supposant la Gaussianité, le bootstrap conduit à des intervalles plus précis dans les cas où la dimension transversale est relativement faible car il prend en considération le biais de l'estimateur des moindres carrés ordinaires comme le montre une étude récente de Gonçalves et Perron (2014). Dans le troisième chapitre, nous suggérons des procédures de sélection convergentes pour les regressions augmentées de facteurs en échantillons finis. Nous démontrons premièrement que la méthode de validation croisée usuelle est non-convergente mais que sa généralisation, la validation croisée «leave-d-out» sélectionne le plus petit ensemble de facteurs estimés pour l'espace généré par les vraies facteurs. Le deuxième critère dont nous montrons également la validité généralise l'approximation bootstrap de Shao (1996) pour les regressions augmentées de facteurs. Les simulations montrent une amélioration de la probabilité de sélectionner par- cimonieusement les facteurs estimés comparativement aux méthodes de sélection disponibles. L'application empirique revisite la relation entre les facteurs macroéconomiques et financiers, et l'excès de rendement sur le marché boursier américain. Parmi les facteurs estimés à partir d'un large panel de données macroéconomiques et financières des États Unis, les facteurs fortement correlés aux écarts de taux d'intérêt et les facteurs de Fama-French ont un bon pouvoir prédictif pour les excès de rendement.