Search results for "pane"

showing 10 items of 1074 documents

Panel Data Analysis via Mechanistic Models

2018

Panel data, also known as longitudinal data, consist of a collection of time series. Each time series, which could itself be multivariate, comprises a sequence of measurements taken on a distinct unit. Mechanistic modeling involves writing down scientifically motivated equations describing the collection of dynamic systems giving rise to the observations on each unit. A defining characteristic of panel systems is that the dynamic interaction between units should be negligible. Panel models therefore consist of a collection of independent stochastic processes, generally linked through shared parameters while also having unit-specific parameters. To give the scientist flexibility in model spe…

FOS: Computer and information sciencesStatistics and ProbabilityMultivariate statisticsSeries (mathematics)Longitudinal dataComputer science05 social sciences01 natural sciencesMethodology (stat.ME)010104 statistics & probabilityNonlinear system0502 economics and business0101 mathematicsStatistics Probability and UncertaintyParticle filterAlgorithmStatistics - Methodology050205 econometrics Panel dataSequence (medicine)Journal of the American Statistical Association
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An ensemble approach to short-term forecast of COVID-19 intensive care occupancy in Italian Regions

2020

Abstract The availability of intensive care beds during the COVID‐19 epidemic is crucial to guarantee the best possible treatment to severely affected patients. In this work we show a simple strategy for short‐term prediction of COVID‐19 intensive care unit (ICU) beds, that has proved very effective during the Italian outbreak in February to May 2020. Our approach is based on an optimal ensemble of two simple methods: a generalized linear mixed regression model, which pools information over different areas, and an area‐specific nonstationary integer autoregressive methodology. Optimal weights are estimated using a leave‐last‐out rationale. The approach has been set up and validated during t…

FOS: Computer and information sciencesStatistics and ProbabilityTime FactorsOccupancyCoronavirus disease 2019 (COVID-19)Computer science01 natural sciencesGeneralized linear mixed modelSARS‐CoV‐2law.inventionclustered data; COVID-19; generalized linear mixed model; integer autoregressive; integer autoregressive model; panel data; SARS-CoV-2; weighted ensembleMethodology (stat.ME)panel data010104 statistics & probability03 medical and health sciences0302 clinical medicinelawCOVID‐19Intensive careEconometricsHumansclustered data030212 general & internal medicine0101 mathematicsPandemicsStatistics - MethodologySARS-CoV-2Reproducibility of ResultsCOVID-19General Medicineweighted ensembleIntensive care unitResearch PapersTerm (time)integer autoregressiveIntensive Care UnitsAutoregressive modelItalyNonlinear Dynamicsgeneralized linear mixed modelinteger autoregressive modelclustered data; COVID-19; generalized linear mixed model; integer autoregressive; integer autoregressive model; panel data; SARS-CoV-2; weighted ensemble; COVID-19; Humans; Intensive Care Units; Italy; Nonlinear Dynamics; Pandemics; Reproducibility of Results; Time Factors; ForecastingStatistics Probability and UncertaintySettore SECS-S/01Settore SECS-S/01 - StatisticaPanel dataResearch PaperForecasting
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Longitudinal factorial invariance of the Maslach Burnout Inventory-General Survey among employees with job-related psychological health problems

2011

The study provides new knowledge about the longitudinal factorial invariance of the Maslach Burnout Inventory-General Survey (MBI-GS). In order to investigate the factor structure of the MBI-GS and its invariance across time, a full panel data with two measurements gathered among employees with job-related psychological health problems was used. Consistent with previous study findings, the results indicated that the correlated three-factor model of the MBI-GS (i.e. exhaustion, cynicism and professional efficacy) showed a better fit with the data than the alternative factor models. The correlated three-factor structure was invariant across time, indicating that the scale has good construct v…

Factorial invarianceConstruct validityGeneral MedicineBurnoutPsychological healthPsychiatry and Mental healthClinical PsychologyCynicismScale (social sciences)PsychologySocial psychologyApplied PsychologyClinical psychologyPanel dataFactor analysisStress and Health
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Elogios del santo rey Don Fernando : puestas en el sepulcro de Sevilla en hebreo y arabigo ... / por ... Henrique Florez ... del Gran Padre S. August…

1754

Caplletres ornades, vinyetes Sign. : A-C4, D3 Reclams

Ferran III rei de Castella sant Panegírics Obres anteriors a 1800
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Elogios del santo rey Don Fernando : puestas en el sepulcro de Sevilla en hebreo y arabigo ...

Caplletres ornades, vinyetes Sign. : A-C4, D3 Reclams

Ferran III rei de Castella-Lleó 1199-1252 Panegírics Obres anteriors al 1800
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Motivi tragici nelle Imagines di Filostrato Maggiore (I 4; 18; 27; II 4; 10; 13; 23; 29; 30).

Grazie all'analisi del rapporto tra il testo delle descrizioni di Filostrato e quello di Seneca tragico, Ovidio e Stazio si ipotizza la presenza nelle Imagines di allusioni ad opere ellenistiche perdute (si fa riferimento a Callimaco e Nicandro) . Inoltre, sulla base di un parallelismo tra II 4 (Ippolito) e un verso delle Rane di Aristofane si rintraccia una citazione dell'Ippolito Velato euripideo. The analysis of the relationship between the Philostratean text and the one of Seneca (only Tragedies), Ovid and Statius confirmed the presence in Philostratus' Imagines of allusions to some Hellenistic lost works (we refer to Callimachus and Nicander) . In addition, thanks to a parallel between…

Filostrato Imagines Euripide Seneca Ovidio Stazio Baccanti Dioniso Ippolito Meneceo Antigone Evadne Capaneo Anfiarao Sette a Tebe Aiace Locrese iconografia.Settore L-FIL-LET/02 - Lingua E Letteratura Greca
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Pecking Order Versus Trade-off: An Empirical Approach to the Small and Medium Enterprise Capital Structure

2003

In this paper, we explore two of the most relevant theories that explain financial policy in small and medium enterprises (SMEs): pecking order theory and trade-off theory. Panel data methodology is used to test the empirical hypotheses over a sample of 6482 Spanish SMEs during the five-year period 1994?1998. The results suggest that both theoretical approaches contribute to explain capital structure in SMEs. However, while we find evidence that SMEs attempt to achieve a target or optimum leverage (trade-off model), there is less support for the view that SMEs adjust their leverage level to their financing requirements (pecking order model). En este trabajo, exploramos dos de las teorías má…

FinanceCapital structurebusiness.industryPecking orderjel:C34Sample (statistics)Trade-offjel:G32jel:G33MicroeconomicsLeverage (negotiation)Pecking order theoryEconomicsSmall and medium-sized enterprisesbusinessselección jerárquica equilibrio estático estructura de capital pymes datos de panel. Pecking Order Trade-off Capital Structure Small and Medium Enterprises Panel Data.Panel dataSSRN Electronic Journal
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Capital Structure and Sensitivity in SME Definition: A Panel Data Investigation

2003

We provide an empirical examination of the pecking order theory on capital structure in the field of Small and Medium Enterprises (SMEs). We mainly investigate if the results are sensitive to different definitions commonly used for these types of companies. Our evidence offers strong support for the growth opportunities and cash flow hypotheses. Firms that have many growth opportunities and small cash flows clearly show more debt in their capital structure. Moreover, results do not change when different SME definitions or sample sizes are used.

FinanceCapital structurebusiness.industrymedia_common.quotation_subjectPecking orderSample size determinationDebtPecking order theoryCash flowBusinessSmall and medium-sized enterprisesIndustrial organizationmedia_commonPanel dataSSRN Electronic Journal
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Monitoring and Market Power in Loan Markets

2000

Whether or not banks are engaged in ex ante monitoring of customers may have important consequences for the whole economy. We approach this question via a model in which banks can invest in either information acquisition or market power (product differentiation). The two alternatives generate different predictions, which are tested using panel data on Finnish local banks. We find evidence that banks’ investments in branch networks and human capital (personnel) contribute to information acquisition but not to market power. We also find that managing customers’ money transactions enhances banks ability to control their lending risks.

FinanceEx-antebusiness.industryControl (management)Product differentiationMonetary economicsjel:D21Human capitaljel:G21banks; information acquisition; market power; fixed costs; branch network; default costsjel:L15LoanEconomicsInformation acquisitionMarket powerbusinessPanel dataSSRN Electronic Journal
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Intellectual capital and the creation of value in Latvian banking sector: panel data analysis

2010

Intellectual capital (IC) has proven to be under valuated in many countries over the world. This paper provides some evidence that Latvia is not an exception. Author has used the research methods applied in the research on financial sector by the Malaysian, Finnish and Brazilian scientists to provide a view to the issues of IC in Latvian banking sector. The study is based on applying calculated intangible value (CIV), which measures the monetary value of IC or IC stock, value-added intellectual coefficient (VAIC™), which describes how a company's IC adds value to the company and intellectual capital efficiency (ICE), which measure the flow of IC. This paper presents the results on the analy…

Financebusiness.industryLatvianAccountingGeneral MedicineHuman capitallanguage.human_languageIntellectual capitalStructural capitalCapital employedlanguageEconomicsbusinessFinancial statementStock (geology)Panel dataAmerican J. of Finance and Accounting
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