A flexible cost function model with risk

In examining bank cost efficiency in banking inclusion of risk-taking of banks is very important. In this paper we depart from the standard modeling approach and view risk intimately related to the technology. Thus, instead of controlling for risk by viewing them as covariates in the standard cost function we argue that the technology differs with risk, thereby meaning that the parameters of the parametric cost function changes with risk in a fully flexible manner. This is accomplished by viewing the parameters of the cost function as nonparametric functions of risk. We also control for country-specific effects in a fully flexible manner by using them as arguments of the nonparametric functions along with the risk variable. The resulting cost function then becomes semiparametric. The standard parametric model becomes a special case of our semiparametric model. We use the above modeling approach for banks in the EU countries. Actually, European financial integration is seen as a stepping stone for the development of a competitive single EU market that promotes efficiency and increases consumer welfare, changing the risk profile of the European banks. Particularly, financial integration allows more risk diversification and permits banks to use more advanced risk management instruments and systems, however it has at the same time increased the probability of systematic risks. Financial integration has increased the risk of contagion and changed its nature and scope. Consequently the bank’s risk seems to be an important issue to be investigated.

Computational Analysis Based on Parametric Models of Historic Masonry Vaulted Structures Strengthened by Fiber-Reinforced Composite Materials

Historic vaulted masonry structures often need strengthening interventions that can effectively improve their structural performance, especially during seismic events, and at the same time respect the existing setting and the modern conservation requirements. In this context, the use of innovative materials such as fiber-reinforced composite materials has been shown as an effective solution that can satisfy both aspects. This work aims to provide insight into the computational modeling of a full-scale masonry vault strengthened by fiber-reinforced composite materials and analyze the influence of the arrangement of the reinforcement on the efficiency of the intervention. At first, a parametric model of a cross vault focusing on a realistic representation of its micro-geometry is proposed. Then numerical modeling, simulating the pushover analyses, of several barrel vaults reinforced with different reinforcement configurations is performed. Finally, the results are collected and discussed in terms of force-displacement curves obtained for each proposed configuration.

Conceptual Design of Monocolumn Production and Storage With Dry Tree Capability

A new concept and a preliminary study for a monocolumn floating unit are introduced, aimed at exploring and producing oil in ultradeep waters. This platform, which combines two relevant features-great oil storage capacity and dry tree production capability-comprises two bodies with relatively independent heave motions between them. A parametric model is used to define the main design characteristics of the floating units. A set of design alternatives is generated using this procedure. These solutions are evaluated in terms of stability requirements and dynamic response. A mathematical model is developed to estimate the first order heave and pitch motions of the platform. Experimental tests are carried out in order to calibrate this model. The response of each body alone is estimated numerically using the WAMIT (R) code. This paper also includes a preliminary study on the platform mooring system and appendages. The study of the heave plates presents the gain, in terms of decreasing the motions, achieved by the introduction of the appropriate appendages to the platform. [DOI: 10.1115/1.4001429]

An analysis of valve re-replacement after aortic valve replacement with biologic devices

Biologic valve re-replacement was examined in a series of 1343 patients who underwent aortic valve replacement at The Prince Charles Hospital, Brisbane, with a cryopreserved or 4 degrees C stored allograft valve or a xenograft valve, A parametric model approach was used to simultaneously model the competing risks of death without re-replacement and re-replacement before death, One hundred eleven patients underwent a first re-replacement for a variety of reasons (69 patients with xenograft valves, 28 patients with 4 degrees C stored allograft valves, and 14 patients with cryopreserved allograft valves), By multivariable analysis younger age at operation was associated with xenograft, 4 degrees C stored allograft, and cryopreserved allograft valve re-replacement, However, this effect was examined in the context of longer survival of younger patients, which increases their exposure to the risk of re-replacement as compared with that in older patients whose decreased survival reduced their probability of requiring valve re-replacement, In patients older than 60 years at the time of aortic valve replacement, the probability of re-replacement (for any reason) before death was similar for xenografts and cryopreserved allograft valves but higher for 4 degrees C stored valves, However, in patients younger than 60 years, the probability of re-replacement at any time during the remainder of the life of the patient was lower with the cryopreserved allograft valve compared with the xenograft valve and 4 degrees C stored allografts.

Relative dispersion of intravascular transit times during isolated human limb perfusions for recurrent melanoma

Aims We have characterized the relative dispersion of vascular and extravascular markers in the limbs of three patients undergoing isolated limb perfusions with the cytotoxic melphalan for recurrent malignant melanoma both before and after melphalan dosing. Methods A bolus of injectate containing [Cr-51] labelled red blood cells, [C-14]-sucrose and [H-3]-water was injected into an iliac or femoral artery and outflow samples collected at 1 s intervals by a fraction collector. The radioactivity due to each isotype was analysed by either gamma [Cr-51] or beta [C-14 and H-3] counting. The moments of the outflow fraction-time profiles were estimated by a nonparametric (numerical integration) method and a parametric model (sum of two inverse Gaussian functions). Results The availability, mean transit time and normalised variance (CV2) obtained for labelled red blood cells, sucrose and water were similar before and after melphalan dosing and with the two methods of calculation but varied between the patients. Conclusions The vascular space is not well-stirred but characterized by a CV2 similar that reported previously for in situ rat hind limb and rat liver perfusions. A flow-limited blood-tissue exchange was observed for the permeating indicators. Administration of melphalan did not influence the distribution characteristics of the indicators.

Estruturas de Suporte de Terras Executadas Com Pneus. Estudo Paramétrico e Conceção de Protótipo

No presente trabalho descreve-se o estudo realizado no Instituto Superior de Engenharia do Porto (ISEP) com o objetivo de comprovar a viabilidade da utilização de pneus em fim de vida em estruturas de solo reforçado. As estruturas de suporte de terras materializadas com pneus preenchidos com solo são usadas em alguns países, sobretudo em estruturas do tipo gravidade. Investiga-se neste trabalho o seu desempenho em estruturas de solo reforçado. Com a finalidade de prever o comportamento da construção, foi utilizado um software desenvolvido pela empresa Canadiana Rocscience, denominado Phase2. Com este software foi possível fazer uma análise paramétrica da secção transversal do modelo, avaliando os esforços e os deslocamentos que se desenvolvem no interior da estrutura, através da utilização do Método dos Elementos Finitos. Foi efetuada uma campanha de ensaios laboratoriais, realizados com amostras de solo retiradas do local de construção do protótipo, com o intuito de caracterizar os parâmetros do solo A definição destes parâmetros tem como objetivo tornar a simulação o mais fidedigna possível. Estruturas de Suporte de Terras Executadas Com Pneus. Estudo Paramétrico e Conceção de Protótipo Como validação da modelação realizada no programa Phase2, o protótipo será devidamente instrumentado com equipamentos de monitorização; a informação recolhida receberá um tratamento posterior e permitirá a calibração do modelo numérico. No presente trabalho define-se o plano de monitorização a instalar no protótipo.

Joint modelling of longitudinal and survival data on breast cancer

Tese de Doutoramento em Ciências (Especialidade em Matemática)

Indirect likelihood inference

Given a sample from a fully specified parametric model, let Zn be a given finite-dimensional statistic - for example, an initial estimator or a set of sample moments. We propose to (re-)estimate the parameters of the model by maximizing the likelihood of Zn. We call this the maximum indirect likelihood (MIL) estimator. We also propose a computationally tractable Bayesian version of the estimator which we refer to as a Bayesian Indirect Likelihood (BIL) estimator. In most cases, the density of the statistic will be of unknown form, and we develop simulated versions of the MIL and BIL estimators. We show that the indirect likelihood estimators are consistent and asymptotically normally distributed, with the same asymptotic variance as that of the corresponding efficient two-step GMM estimator based on the same statistic. However, our likelihood-based estimators, by taking into account the full finite-sample distribution of the statistic, are higher order efficient relative to GMM-type estimators. Furthermore, in many cases they enjoy a bias reduction property similar to that of the indirect inference estimator. Monte Carlo results for a number of applications including dynamic and nonlinear panel data models, a structural auction model and two DSGE models show that the proposed estimators indeed have attractive finite sample properties.

Fourth order pseudo maximum likelihood methods

We extend PML theory to account for information on the conditional moments up to order four, but without assuming a parametric model, to avoid a risk of misspecification of the conditional distribution. The key statistical tool is the quartic exponential family, which allows us to generalize the PML2 and QGPML1 methods proposed in Gourieroux et al. (1984) to PML4 and QGPML2 methods, respectively. An asymptotic theory is developed. The key numerical tool that we use is the Gauss-Freud integration scheme that solves a computational problem that has previously been raised in several fields. Simulation exercises demonstrate the feasibility and robustness of the methods [Authors]

The truncated mean of an asymmetric distribution

This paper investigates a simple procedure to estimate robustly the mean of an asymmetric distribution. The procedure removes the observations which are larger or smaller than certain limits and takes the arithmetic mean of the remaining observations, the limits being determined with the help of a parametric model, e.g., the Gamma, the Weibull or the Lognormal distribution. The breakdown point, the influence function, the (asymptotic) variance, and the contamination bias of this estimator are explored and compared numerically with those of competing estimates.

Generation of Simulated Daily Precipitation and Air and Soil Temperatures, January 2000

This paper describes a maximum likelihood method using historical weather data to estimate a parametric model of daily precipitation and maximum and minimum air temperatures. Parameter estimates are reported for Brookings, SD, and Boone, IA, to illustrate the procedure. The use of this parametric model to generate stochastic time series of daily weather is then summarized. A soil temperature model is described that determines daily average, maximum, and minimum soil temperatures based on air temperatures and precipitation, following a lagged process due to soil heat storage and other factors.

Bayesian Networks for the Age Classification of Living Individuals: a Study on Transition Analysis

Over the past few decades, age estimation of living persons has represented a challenging task for many forensic services worldwide. In general, the process for age estimation includes the observation of the degree of maturity reached by some physical attributes, such as dentition or several ossification centers. The estimated chronological age or the probability that an individual belongs to a meaningful class of ages is then obtained from the observed degree of maturity by means of various statistical methods. Among these methods, those developed in a Bayesian framework offer to users the possibility of coherently dealing with the uncertainty associated with age estimation and of assessing in a transparent and logical way the probability that an examined individual is younger or older than a given age threshold. Recently, a Bayesian network for age estimation has been presented in scientific literature; this kind of probabilistic graphical tool may facilitate the use of the probabilistic approach. Probabilities of interest in the network are assigned by means of transition analysis, a statistical parametric model, which links the chronological age and the degree of maturity by means of specific regression models, such as logit or probit models. Since different regression models can be employed in transition analysis, the aim of this paper is to study the influence of the model in the classification of individuals. The analysis was performed using a dataset related to the ossifications status of the medial clavicular epiphysis and results support that the classification of individuals is not dependent on the choice of the regression model.

Broadband excitation in the system identification of active magnetic bearing rotor systems

One of the targets of the climate and energy package of the European Union is to increase the energy efficiency in order to achieve a 20 percent reduction in primary energy use compared with the projected level by 2020. The energy efficiency can be improved for example by increasing the rotational speed of large electrical drives, because this enables the elimination of gearboxes leading to a compact design with lower losses. The rotational speeds of traditional bearings, such as roller bearings, are limited by mechanical friction. Active magnetic bearings (AMBs), on the other hand, allow very high rotational speeds. Consequently, their use in large medium- and high-speed machines has rapidly increased. An active magnetic bearing rotor system is an inherently unstable, nonlinear multiple-input, multiple-output system. Model-based controller design of AMBs requires an accurate system model. Finite element modeling (FEM) together with the experimental modal analysis provides a very accurate model for the rotor, and a linearized model of the magneticactuators has proven to work well in normal conditions. However, the overall system may suffer from unmodeled dynamics, such as dynamics of foundation or shrink fits. This dynamics can be modeled by system identification. System identification can also be used for on-line diagnostics. In this study, broadband excitation signals are adopted to the identification of an active magnetic bearing rotor system. The broadband excitation enables faster frequency response function measurements when compared with the widely used stepped sine and swept sine excitations. Different broadband excitations are reviewed, and the random phase multisine excitation is chosen for further study. The measurement times using the multisine excitation and the stepped sine excitation are compared. An excitation signal design with an analysis of the harmonics produced by the nonlinear system is presented. The suitability of different frequency response function estimators for an AMB rotor system are also compared. Additionally, analytical modeling of an AMB rotor system, obtaining a parametric model from the nonparametric frequency response functions, and model updating are discussed in brief, as they are key elements in the modeling for a control design. Theoretical methods are tested with a laboratory test rig. The results conclude that an appropriately designed random phase multisine excitation is suitable for the identification of AMB rotor systems.

Parametrisen kustannusmallin validointi ja implementointi

Parametric cost modeling is a technique, where cost estimating relationships are built to meet products’ parameters. Parameters are directly defined from product features, when it is possible to solve product cost exact before even a single product is manufactured and calculated with general cost accounting. The parametric model can be used in product design, sourcing and comparing product cost of similar products. The model reveals the cost origin more clear than general accounting. The purpose of this thesis was to find out parameters for modeling elevator doors and validate the parameters to meet actual costs. The other target was to simulate cost impact and changes in the cost structure. The results were compared to previous calculations and actual costs and model was tested in new product design. The results of the calculations revealed, that material consumption is the most significant issue in design effectiveness as well as the complexity of the components and structure. To develop the model more research is needed for other continents cost structure and waste calculation principles.

Efficient estimation using the characteristic function : theory and applications with high frequency data

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