903 resultados para Variable splitting augmented Lagrangian


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El objetivo de este trabajo consiste en proponer una medida de performance adecuada para los fondos de inversión de renta variable. Las características específicas de este tipo de carteras inducen a tomar un enfoque basado en la L.M.C., por lo que se escoge como medida de riesgo el riesgo total de la cartera (pσ). Se introducen las estrategias pasivas y activas en el análisis, con lo que se consigue desarrollar una medida de performance que, además de medir la rentabilidad por gestión efectiva, la pondera en función del grado de actividad asumido por la cartera a evaluar.

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Given a model that can be simulated, conditional moments at a trial parameter value can be calculated with high accuracy by applying kernel smoothing methods to a long simulation. With such conditional moments in hand, standard method of moments techniques can be used to estimate the parameter. Since conditional moments are calculated using kernel smoothing rather than simple averaging, it is not necessary that the model be simulable subject to the conditioning information that is used to define the moment conditions. For this reason, the proposed estimator is applicable to general dynamic latent variable models. Monte Carlo results show that the estimator performs well in comparison to other estimators that have been proposed for estimation of general DLV models.

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The mechanisms responsible for cytokinesis and its coordination with other events of the cell cycle are poorly understood. Genetic studies of cytokinesis in fission yeast are one useful approach to this problem. A number of conditional mutants of fission yeast that show defects in the formation of the septum of cytokinesis have been identified. Cloning of the genes affected in these mutants has begun to shed light upon the elements required to direct the construction of the division septum and also upon how the initiation of septum formation may be coordinated with mitosis.

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Report for the scientific sojourn at the James Cook University, Australia, between June to December 2007. Free convection in enclosed spaces is found widely in natural and industrial systems. It is a topic of primary interest because in many systems it provides the largest resistance to the heat transfer in comparison with other heat transfer modes. In such systems the convection is driven by a density gradient within the fluid, which, usually, is produced by a temperature difference between the fluid and surrounding walls. In the oil industry, the oil, which has High Prandtl, usually is stored and transported in large tanks at temperatures high enough to keep its viscosity and, thus the pumping requirements, to a reasonable level. A temperature difference between the fluid and the walls of the container may give rise to the unsteady buoyancy force and hence the unsteady natural convection. In the initial period of cooling the natural convection regime dominates over the conduction contribution. As the oil cools down it typically becomes more viscous and this increase of viscosity inhibits the convection. At this point the oil viscosity becomes very large and unloading of the tank becomes very difficult. For this reason it is of primary interest to be able to predict the cooling rate of the oil. The general objective of this work is to develop and validate a simulation tool able to predict the cooling rates of high Prandtl fluid considering the variable viscosity effects.

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This paper develops methods for Stochastic Search Variable Selection (currently popular with regression and Vector Autoregressive models) for Vector Error Correction models where there are many possible restrictions on the cointegration space. We show how this allows the researcher to begin with a single unrestricted model and either do model selection or model averaging in an automatic and computationally efficient manner. We apply our methods to a large UK macroeconomic model.

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This paper develops stochastic search variable selection (SSVS) for zero-inflated count models which are commonly used in health economics. This allows for either model averaging or model selection in situations with many potential regressors. The proposed techniques are applied to a data set from Germany considering the demand for health care. A package for the free statistical software environment R is provided.

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The Scottish Parliament has the authority to make a balanced-budget expansion or contraction in public expenditure, funded by corresponding local changes in the basic rate of income tax of up to 3p in the pound. This fiscal adjustment is known as the Scottish Variable Rate of income tax, though it has never, as yet, been used. In this paper we attempt to identify the impact on aggregate economic activity in Scotland of implementing these devolved fiscal powers. This is achieved through theoretical analysis and simulation using a Computable General Equilibrium (CGE) model for Scotland. This analysis generalises the conventional Keynesian model so that negative balanced-budget multipliers values are possible, reflecting a regional “inverted Haavelmo effect”. Key parameters determining the aggregate economic impact are the extent to which the Scottish Government create local amenities valuable to the Scottish population and the extent to which this is incorporated into local wage bargaining.

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This paper considers the instrumental variable regression model when there is uncertainty about the set of instruments, exogeneity restrictions, the validity of identifying restrictions and the set of exogenous regressors. This uncertainty can result in a huge number of models. To avoid statistical problems associated with standard model selection procedures, we develop a reversible jump Markov chain Monte Carlo algorithm that allows us to do Bayesian model averaging. The algorithm is very exible and can be easily adapted to analyze any of the di¤erent priors that have been proposed in the Bayesian instrumental variables literature. We show how to calculate the probability of any relevant restriction (e.g. the posterior probability that over-identifying restrictions hold) and discuss diagnostic checking using the posterior distribution of discrepancy vectors. We illustrate our methods in a returns-to-schooling application.

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We use factor augmented vector autoregressive models with time-varying coefficients to construct a financial conditions index. The time-variation in the parameters allows for the weights attached to each financial variable in the index to evolve over time. Furthermore, we develop methods for dynamic model averaging or selection which allow the financial variables entering into the FCI to change over time. We discuss why such extensions of the existing literature are important and show them to be so in an empirical application involving a wide range of financial variables.

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Los patrones de tomate se han propuesto como una alternativa no química al uso del bromuro de metilo. En este estudio se evaluó la respuesta de resistencia de diez patrones de tomate (comerciales y experimentales) a nematodos del género Meloidogyne mediante un ensayo de campo realizado en un invernadero de plástico cuyo suelo se hallaba infestado por Meloidogyne javanica. Al finalizar la campaña agrícola (marzo a julio), siete de los patrones ensayados mostraron altos niveles de resistencia, uno presentó resistencia intermedia y dos resultaron ser susceptibles al nematodo.

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ABSTRACT: BACKGROUND: Valganciclovir, the oral prodrug of ganciclovir, has been demonstrated equivalent to iv ganciclovir for CMV disease treatment in solid organ transplant recipients. Variability in ganciclovir exposure achieved with valganciclovir could be implicated as a contributing factor for explaining variations in the therapeutic response. This prospective observational study aimed to correlate clinical and cytomegalovirus (CMV) viral load response (DNAemia) with ganciclovir plasma concentrations in patients treated with valganciclovir for CMV infection/disease. METHODS: Seven CMV D+/R- transplant recipients (4 kidney, 2 liver and 1 heart) were treated with valganciclovir (initial dose was 900-1800 mg/day for 3-6.5 weeks, followed by 450-900 mg/day for 2-9 weeks). DNAemia was monitored by real time quantitative PCR and ganciclovir plasma concentration was measured at trough (Ctrough) and 3 h after drug administration (C3h) by HPLC. RESULTS: Four patients presented with CMV syndrome, two had CMV tissue-invasive disease after prophylaxis discontinuation, and one liver recipient was treated pre-emptively for asymptomatic rising CMV viral load 5 weeks post-transplantation in the absence of prophylaxis. CMV DNAemia decreased during the first week of treatment in all recipients except in one patient (median decrease: -1.2 log copies/mL, range: -1.8 to 0) despite satisfactory ganciclovir exposure (AUC0-12 = 48 mg.h/L, range for the 7 patients: 40-118 mg.h/L). Viral clearance was obtained in five patients after a median of time of 34 days (range: 28-82 days). Two patients had recurrent CMV disease despite adequate ganciclovir exposure (65 mg.h/L, range: 44-118 mg.h/L). CONCLUSIONS: Valganciclovir treatment for CMV infection/disease in D+/R- transplant recipients can thus result in variable viral clearance despite adequate ganciclovir plasma concentrations, probably correlating inversely with anti-CMV immune responses after primary infection.

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The McMillan map is a one-parameter family of integrable symplectic maps of the plane, for which the origin is a hyperbolic fixed point with a homoclinic loop, with small Lyapunov exponent when the parameter is small. We consider a perturbation of the McMillan map for which we show that the loop breaks in two invariant curves which are exponentially close one to the other and which intersect transversely along two primary homoclinic orbits. We compute the asymptotic expansion of several quantities related to the splitting, namely the Lazutkin invariant and the area of the lobe between two consecutive primary homoclinic points. Complex matching techniques are in the core of this work. The coefficients involved in the expansion have a resurgent origin, as shown in [MSS08].

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The paper seeks to shed light on inflation dynamics of four new EU member states: the Czech Republic, Hungary, Poland and Slovakia. To this end, the New Keynesian Phillips curve augmented for open economies is estimated and additional statistical tests applied. We find the following. (1) The claim of New Keynesians that the real marginal cost is the main inflation-forcing variable is fragile. (2) Inflation seems to be driven by external factors. (3) Although inflation holds a forward-looking component, the backward-looking component is substantial. An intuitive explanation for higher inflation persistence may be rather adaptive than rational price setting of local firms.