Data-driven system identification via evolutionary retrieval of Takagi-Sugeno fuzzy models

Systemidentification, evolutionary automatic, data-driven model, fuzzy Takagi-Sugeno grammar, genotype interpretability, toxicity-prediction

Development and Validation of Predictive Models of Cardiac Mortality and Transplantation in Resynchronization Therapy

AbstractBackground:30-40% of cardiac resynchronization therapy cases do not achieve favorable outcomes.Objective:This study aimed to develop predictive models for the combined endpoint of cardiac death and transplantation (Tx) at different stages of cardiac resynchronization therapy (CRT).Methods:Prospective observational study of 116 patients aged 64.8 ± 11.1 years, 68.1% of whom had functional class (FC) III and 31.9% had ambulatory class IV. Clinical, electrocardiographic and echocardiographic variables were assessed by using Cox regression and Kaplan-Meier curves.Results:The cardiac mortality/Tx rate was 16.3% during the follow-up period of 34.0 ± 17.9 months. Prior to implantation, right ventricular dysfunction (RVD), ejection fraction < 25% and use of high doses of diuretics (HDD) increased the risk of cardiac death and Tx by 3.9-, 4.8-, and 5.9-fold, respectively. In the first year after CRT, RVD, HDD and hospitalization due to congestive heart failure increased the risk of death at hazard ratios of 3.5, 5.3, and 12.5, respectively. In the second year after CRT, RVD and FC III/IV were significant risk factors of mortality in the multivariate Cox model. The accuracy rates of the models were 84.6% at preimplantation, 93% in the first year after CRT, and 90.5% in the second year after CRT. The models were validated by bootstrapping.Conclusion:We developed predictive models of cardiac death and Tx at different stages of CRT based on the analysis of simple and easily obtainable clinical and echocardiographic variables. The models showed good accuracy and adjustment, were validated internally, and are useful in the selection, monitoring and counseling of patients indicated for CRT.

Financial intermediation in a model of growth through creative destruction

This paper presents an endogenous growth model in which the research activity is financed by intermediaries that are able to reduce the incidence of researcher's moral hazard. It is shown that financial activity is growth promoting because it increases research productivity. It is also found that a subsidy to the financial sector may have larger growth effects than a direct subsidy to research. Moreover, due to the presence of moral hazard, increasing the subsidy rate to R\&D may reduce the growth rate. I show that there exists a negative relation between the financing of innovation and the process of capital accumulation. Concerning welfare, the presence of two externalities of opposite sign steaming from financial activity may cause that the no-tax equilibrium provides an inefficient level of financial services. Thus, policies oriented to balance the effects of the two externalities will be welfare improving.

Generalized factor models: a bayesian approach

There is recent interest in the generalization of classical factor models in which the idiosyncratic factors are assumed to be orthogonal and there are identification restrictions on cross-sectional and time dimensions. In this study, we describe and implement a Bayesian approach to generalized factor models. A flexible framework is developed to determine the variations attributed to common and idiosyncratic factors. We also propose a unique methodology to select the (generalized) factor model that best fits a given set of data. Applying the proposed methodology to the simulated data and the foreign exchange rate data, we provide a comparative analysis between the classical and generalized factor models. We find that when there is a shift from classical to generalized, there are significant changes in the estimates of the structures of the covariance and correlation matrices while there are less dramatic changes in the estimates of the factor loadings and the variation attributed to common factors.

A nonlinear threshold model for the dependence of extremes of stationary sequences

One of the main implications of the efficient market hypothesis (EMH) is that expected future returns on financial assets are not predictable if investors are risk neutral. In this paper we argue that financial time series offer more information than that this hypothesis seems to supply. In particular we postulate that runs of very large returns can be predictable for small time periods. In order to prove this we propose a TAR(3,1)-GARCH(1,1) model that is able to describe two different types of extreme events: a first type generated by large uncertainty regimes where runs of extremes are not predictable and a second type where extremes come from isolated dread/joy events. This model is new in the literature in nonlinear processes. Its novelty resides on two features of the model that make it different from previous TAR methodologies. The regimes are motivated by the occurrence of extreme values and the threshold variable is defined by the shock affecting the process in the preceding period. In this way this model is able to uncover dependence and clustering of extremes in high as well as in low volatility periods. This model is tested with data from General Motors stocks prices corresponding to two crises that had a substantial impact in financial markets worldwide; the Black Monday of October 1987 and September 11th, 2001. By analyzing the periods around these crises we find evidence of statistical significance of our model and thereby of predictability of extremes for September 11th but not for Black Monday. These findings support the hypotheses of a big negative event producing runs of negative returns in the first case, and of the burst of a worldwide stock market bubble in the second example. JEL classification: C12; C15; C22; C51 Keywords and Phrases: asymmetries, crises, extreme values, hypothesis testing, leverage effect, nonlinearities, threshold models

Validation de la version française du questionnaire I7 d'impulsivité. Influence de la personnalité, du sexe et de la religion = Validation of the french version of the eysenck's impulsiveness questionnaire (I7). Influence of personality, gender, and religion

L'objectif de cette étude est de vérifier la validité interne de la version française du questionnaire d'impulsivité d'Eysenck (I7), traduite par Dupont et al., sur un échantillon d'étudiants suisses (n = 220). Dans leur questionnaire, Eysenck et Eysenck proposent trois échelles : les deux premières évaluant deux composantes distinctes de l'impulsivité (l'Impulsivité caractérisant les individus qui agissent sans penser, sans être conscients des risques associés à leurs actions, et la Recherche d'aventure caractérisant les individus qui agissent en étant conscients, et en tenant compte des risques associés à leurs actions), et la troisième servant de « distracteur » (l'Empathie caractérisant les individus qui ont la faculté de s'identifier à l'autre). La structure à trois facteurs de l'instrument a été confirmée par notre analyse factorielle en composantes principales. La solution factorielle retenue n'explique toutefois qu'une faible proportion de la variance (21.9 %). L'homogénéité interne des échelles, mesurée à l'aide d'alphas de Cronbach, est acceptable pour l'échelle d'Impulsivité (.78) et de Recherche d'aventure (.71), mais elle est, en revanche, faible pour l'échelle d'Empathie (.62). Les échelles de l'I7 d'Eysenck entretiennent des corrélations cohérentes avec les cinq grandes dimensions de la personnalité mesurées par le NEO PI-R. L'Impulsivité est associée négativement à la dimension Conscience (r = - .32), alors que la Recherche d'aventures est associée positivement à la dimension Extraversion (r = .33). Le sexe a un impact sur les échelles Recherche d'aventure et Empathie. Les qualités métrologiques de la version française du questionnaire d'impulsivité d'Eysenck (I7) sont satisfaisantes, mais l'estimation d'autres indices de validité, comme la fidélité test-retest et la validité convergente, devrait être réalisée.

A General model of bilateral migration agreements

Unilateral migration policies impose externalities on other countries. In order to try to internalize these externalities, countries sign bilateral migration agreements. One element of these agreements is the emphasis on enforcing migration policies: immigrant-receiving countries agree to allow more immigrants from their emigrant-sending partner if they cooperate in enforcing their migration policy at the border. I present a simple theoretical model that justifies this behavior in a two-country setting with welfare maximizing governments. These governments establish migration quotas that need to be enforced at a cost. I prove that uncoordinated migration policies are inefficient. Both countries can improve welfare by exchanging a more "generous" migration quota for expenditure on enforcement policy. Contrary to what could be expected, this result does not depend on the enforcement technology that both countries employ.

Structural analysis of Turtle mountain (Alberta) using digital elevation model: Toward a progressive failure

In 1903, the eastern slope of Turtle Mountain (Alberta) was affected by a 30 M m3-rockslide named Frank Slide that resulted in more than 70 casualties. Assuming that the main discontinuity sets, including bedding, control part of the slope morphology, the structural features of Turtle Mountain were investigated using a digital elevation model (DEM). Using new landscape analysis techniques, we have identified three main joint and fault sets. These results are in agreement with those sets identified through field observations. Landscape analysis techniques, using a DEM, confirm and refine the most recent geology model of the Frank Slide. The rockslide was initiated along bedding and a fault at the base of the slope and propagated up slope by a regressive process following a surface composed of pre-existing discontinuities. The DEM analysis also permits the identification of important geological structures along the 1903 slide scar. Based on the so called Sloping Local Base Level (SLBL) an estimation was made of the present unstable volumes in the main scar delimited by the cracks, and around the south area of the scar (South Peak). The SLBL is a method permitting a geometric interpretation of the failure surface based on a DEM. Finally we propose a failure mechanism permitting the progressive failure of the rock mass that considers gentle dipping wedges (30°). The prisms or wedges defined by two discontinuity sets permit the creation of a failure surface by progressive failure. Such structures are more commonly observed in recent rockslides. This method is efficient and is recommended as a preliminary analysis prior to field investigation.

Can a Lucas model with habit generate realistic conditional volatility in exchange rate returns?

In this paper, we attempt to give a theoretical underpinning to the well established empirical stylized fact that asset returns in general and the spot FOREX returns in particular display predictable volatility characteristics. Adopting Moore and Roche s habit persistence version of Lucas model we nd that both the innovation in the spot FOREX return and the FOREX return itself follow "ARCH" style processes. Using the impulse response functions (IRFs) we show that the baseline simulated FOREX series has "ARCH" properties in the quarterly frequency that match well the "ARCH" properties of the empirical monthly estimations in that when we scale the x-axis to synchronize the monthly and quarterly responses we find similar impulse responses to one unit shock in variance. The IRFs for the ARCH processes we estimate "look the same" with an approximately monotonic decreasing fashion. The Lucas two-country monetary model with habit can generate realistic conditional volatility in spot FOREX return.

A comparison of results from MRIO and interregional computable general equilibrium (CGE) analyses of the impacts of a positive demand shock on the ‘CO2 trade balance’ between Scotland and the rest of the UK

In previous work we have applied the environmental multi-region input-output (MRIO) method proposed by Turner et al (2007) to examine the ‘CO2 trade balance’ between Scotland and the Rest of the UK. In McGregor et al (2008) we construct an interregional economy-environment input-output (IO) and social accounting matrix (SAM) framework that allows us to investigate methods of attributing responsibility for pollution generation in the UK at the regional level. This facilitates analysis of the nature and significance of environmental spillovers and the existence of an environmental ‘trade balance’ between regions. While the existence of significant data problems mean that the quantitative results of this study should be regarded as provisional, we argue that the use of such a framework allows us to begin to consider questions such as the extent to which a devolved authority like the Scottish Parliament can and should be responsible for contributing to national targets for reductions in emissions levels (e.g. the UK commitment to the Kyoto Protocol) when it is limited in the way it can control emissions, particularly with respect to changes in demand elsewhere in the UK. However, while such analysis is useful in terms of accounting for pollution flows in the single time period that the accounts relate to, it is limited when the focus is on modelling the impacts of any marginal change in activity. This is because a conventional demand-driven IO model assumes an entirely passive supply-side in the economy (i.e. all supply is infinitely elastic) and is further restricted by the assumption of universal Leontief (fixed proportions) technology implied by the use of the A and multiplier matrices. In this paper we argue that where analysis of marginal changes in activity is required, a more flexible interregional computable general equilibrium approach that models behavioural relationships in a more realistic and theory-consistent manner, is more appropriate and informative. To illustrate our analysis, we compare the results of introducing a positive demand stimulus in the UK economy using both IO and CGE interregional models of Scotland and the rest of the UK. In the case of the latter, we demonstrate how more theory consistent modelling of both demand and supply side behaviour at the regional and national levels affect model results, including the impact on the interregional CO2 ‘trade balance’.

Two different 3D biogeochemical models for the NW mediterranean sea: validation with Meris data and intercomparison

Report for the scientific sojourn carried out at the University of New South Wales from February to June the 2007. Two different biogeochemical models are coupled to a three dimensional configuration of the Princeton Ocean Model (POM) for the Northwestern Mediterranean Sea (Ahumada and Cruzado, 2007). The first biogeochemical model (BLANES) is the three-dimensional version of the model described by Bahamon and Cruzado (2003) and computes the nitrogen fluxes through six compartments using semi-empirical descriptions of biological processes. The second biogeochemical model (BIOMEC) is the biomechanical NPZD model described in Baird et al. (2004), which uses a combination of physiological and physical descriptions to quantify the rates of planktonic interactions. Physical descriptions include, for example, the diffusion of nutrients to phytoplankton cells and the encounter rate of predators and prey. The link between physical and biogeochemical processes in both models is expressed by the advection-diffusion of the non-conservative tracers. The similarities in the mathematical formulation of the biogeochemical processes in the two models are exploited to determine the parameter set for the biomechanical model that best fits the parameter set used in the first model. Three years of integration have been carried out for each model to reach the so called perpetual year run for biogeochemical conditions. Outputs from both models are averaged monthly and then compared to remote sensing images obtained from sensor MERIS for chlorophyll.

Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy

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.

The Taylor Principle and (In-) Determinacy in a New Keynesian Model with hiring Frictions and Skill Loss

We introduce duration dependent skill decay among the unemployed into a New-Keynesian model with hiring frictions developed by Blanchard/Gali (2008). If the central bank responds only to (current, lagged or expected future) inflation and quarterly skill decay is above a threshold level, determinacy requires a coefficient on inflation smaller than one. The threshold level is plausible with little steady-state hiring and firing ("Continental European Calibration") but implausibly high in the opposite case ("American calibration"). Neither interest rate smoothing nor responding to the output gap helps to restore determinacy if skill decay exceeds the threshold level. However, a modest response to unemployment guarantees determinacy. Moreover, under indeterminacy, both an adverse sunspot shock and an adverse technology shock increase unemployment extremely persistently.

Transcriptional response to cardiac injury in the zebrafish: systematic identification of genes with highly concordant activity across in vivo models.

BACKGROUND: Zebrafish is a clinically-relevant model of heart regeneration. Unlike mammals, it has a remarkable heart repair capacity after injury, and promises novel translational applications. Amputation and cryoinjury models are key research tools for understanding injury response and regeneration in vivo. An understanding of the transcriptional responses following injury is needed to identify key players of heart tissue repair, as well as potential targets for boosting this property in humans. RESULTS: We investigated amputation and cryoinjury in vivo models of heart damage in the zebrafish through unbiased, integrative analyses of independent molecular datasets. To detect genes with potential biological roles, we derived computational prediction models with microarray data from heart amputation experiments. We focused on a top-ranked set of genes highly activated in the early post-injury stage, whose activity was further verified in independent microarray datasets. Next, we performed independent validations of expression responses with qPCR in a cryoinjury model. Across in vivo models, the top candidates showed highly concordant responses at 1 and 3 days post-injury, which highlights the predictive power of our analysis strategies and the possible biological relevance of these genes. Top candidates are significantly involved in cell fate specification and differentiation, and include heart failure markers such as periostin, as well as potential new targets for heart regeneration. For example, ptgis and ca2 were overexpressed, while usp2a, a regulator of the p53 pathway, was down-regulated in our in vivo models. Interestingly, a high activity of ptgis and ca2 has been previously observed in failing hearts from rats and humans. CONCLUSIONS: We identified genes with potential critical roles in the response to cardiac damage in the zebrafish. Their transcriptional activities are reproducible in different in vivo models of cardiac injury.

Fear of model misspecifcation and the robustness premium

Robust decision making implies welfare costs or robustness premia when the approximating model is the true data generating process. To examine the importance of these premia at the aggregate level we employ a simple two-sector dynamic general equilibrium model with human capital and introduce an additional form of precautionary behavior. The latter arises from the robust decision maker s ability to reduce the effects of model misspecification through allocating time and existing human capital to this end. We find that the extent of the robustness premia critically depends on the productivity of time relative to that of human capital. When the relative efficiency of time is low, despite transitory welfare costs, there are gains from following robust policies in the long-run. In contrast, high relative productivity of time implies misallocation costs that remain even in the long-run. Finally, depending on the technology used to reduce model uncertainty, we fi nd that while increasing the fear of model misspecfi cation leads to a net increase in precautionary behavior, investment and output can fall.