Testing for unit roots in bounded time series

Many key economic and financial series are bounded either by construction or through policy controls. Conventional unit root tests are potentially unreliable in the presence of bounds, since they tend to over-reject the null hypothesis of a unit root, even asymptotically. So far, very little work has been undertaken to develop unit root tests which can be applied to bounded time series. In this paper we address this gap in the literature by proposing unit root tests which are valid in the presence of bounds. We present new augmented Dickey–Fuller type tests as well as new versions of the modified ‘M’ tests developed by Ng and Perron [Ng, S., Perron, P., 2001. LAG length selection and the construction of unit root tests with good size and power. Econometrica 69, 1519–1554] and demonstrate how these tests, combined with a simulation-based method to retrieve the relevant critical values, make it possible to control size asymptotically. A Monte Carlo study suggests that the proposed tests perform well in finite samples. Moreover, the tests outperform the Phillips–Perron type tests originally proposed in Cavaliere [Cavaliere, G., 2005. Limited time series with a unit root. Econometric Theory 21, 907–945]. An illustrative application to U.S. interest rate data is provided

A new calibrated sunspot group series since 1749: statistics of active day fractions

Although the sunspot-number series have existed since the mid-19th century, they are still the subject of intense debate, with the largest uncertainty being related to the "calibration" of the visual acuity of individual observers in the past. Daisy-chain regression methods are applied to inter-calibrate the observers which may lead to significant bias and error accumulation. Here we present a novel method to calibrate the visual acuity of the key observers to the reference data set of Royal Greenwich Observatory sunspot groups for the period 1900-1976, using the statistics of the active-day fraction. For each observer we independently evaluate their observational thresholds [S_S] defined such that the observer is assumed to miss all of the groups with an area smaller than S_S and report all the groups larger than S_S. Next, using a Monte-Carlo method we construct, from the reference data set, a correction matrix for each observer. The correction matrices are significantly non-linear and cannot be approximated by a linear regression or proportionality. We emphasize that corrections based on a linear proportionality between annually averaged data lead to serious biases and distortions of the data. The correction matrices are applied to the original sunspot group records for each day, and finally the composite corrected series is produced for the period since 1748. The corrected series displays secular minima around 1800 (Dalton minimum) and 1900 (Gleissberg minimum), as well as the Modern grand maximum of activity in the second half of the 20th century. The uniqueness of the grand maximum is confirmed for the last 250 years. It is shown that the adoption of a linear relationship between the data of Wolf and Wolfer results in grossly inflated group numbers in the 18th and 19th centuries in some reconstructions.

Fragment-Based QSAR and Molecular Modeling Studies on a Series of Discodermolide Analogs as Microtubule-Stabilizing Anticancer Agents

Inhibition of microtubule function is an attractive rational approach to anticancer therapy. Although taxanes are the most prominent among the microtubule-stabilizers, their clinical toxicity, poor pharmacokinetic properties, and resistance have stimulated the search for new antitumor agents having the same mechanism of action. Discodermolide is an example of nontaxane natural product that has the same mechanism of action, demonstrating superior antitumor efficacy and therapeutic index. The extraordinary chemical and biological properties have qualified discodermolide as a lead structure for the design of novel anticancer agents with optimized therapeutic properties. In the present work, we have employed a specialized fragment-based method to develop robust quantitative structure - activity relationship models for a series of synthetic discodermolide analogs. The generated molecular recognition patterns were combined with three-dimensional molecular modeling studies as a fundamental step on the path to understanding the molecular basis of drug-receptor interactions within this important series of potent antitumoral agents.

Quantitative structure-activity studies on a series of migrastatin analogs as inhibitors of cancer cell metastasis

Migrastatin, a macrolide natural product, and its structurally related analogs are potent inhibitors of cancer cell metastasis, invasion and migration. In the present work, a specialized fragment-based method was employed to develop QSAR models for a series of migrastatin and isomigrastatin analogs. Significant correlation coefficients were obtained (best model, q(2) = 0.76 and r(2) = 0.91) indicating that the QSAR models possess high internal consistency. The best model was then used to predict the potency of an external test set, and the predicted values were in good agreement with the experimental results (R(2) (pred) = 0.85). The final model and the corresponding contribution maps, combined with molecular modeling studies, provided important insights into the key structural features for the anticancer activity of this family of synthetic compounds based on natural products.

Comparative molecular field analysis of a series of inhibitors of HIV-1 protease

Several protease inhibitors have reached the world market in the last fifteen years, dramatically improving the quality of life and life expectancy of millions of HIV-infected patients. In spite of the tremendous research efforts in this area, resistant HIV-1 variants are constantly decreasing the ability of the drugs to efficiently inhibit the enzyme. As a consequence, inhibitors with novel frameworks are necessary to circumvent resistance to chemotherapy. In the present work, we have created 3D QSAR models for a series of 82 HIV-1 protease inhibitors employing the comparative molecular field analysis (CoMFA) method. Significant correlation coefficients were obtained (q(2) = 0.82 and r(2) = 0.97), indicating the internal consistency of the best model, which was then used to evaluate an external test set containing 17 compounds. The predicted values were in good agreement with the experimental results, showing the robustness of the model and its substantial predictive power for untested compounds. The final QSAR model and the information gathered from the CoMFA contour maps should be useful for the design of novel anti-HIV agents with improved potency.

EVALUATION OF METAL TOXICITY BY A MODIFIED METHOD BASED ON THE FUNGUS GERRONEMA VIRIDILUCENS BIOLUMINESCENCE IN AGAR MEDIUM

Metal cation toxicity to basidiomycete fungi is poorly understood, despite its well-known importance in terrestrial ecosystems. Moreover, there is no reported methodology for the routine evaluation of metal toxicity to basidiomycetes. In the present study, we describe the development of a procedure to assess the acute toxicity of metal cations (Na(+), K(+), Li(+), Ca(2+), Mg(2+), Co(2+), Zn(2+), Ni(2+), Mn(2+), Cd(2+), and Cu(2+)) to the bioluminescent basidiomycete fungus Gerronema viridilucens. The method is based on the decrease in the intensity of bioluminescence resulting from injuries sustained by the fungus mycelium exposed to either essential or nonessential metal toxicants. The assay described herein enables LIS to propose a metal toxicity series to Gerronenia viridilucens based on data obtained from the bioluminescence intensity (median effective concentration [EC50] values) versus metal concentration: Cd(2+) > Cu(2+) > Mn(2+) approximate to Ni(2+) approximate to Co(2+) > Zn(2+) > Mg(2+) > Li(+) > K(+) approximate to Na(+) > Ca(2+), and to shed some li-ht on the mechanism of toxic action of metal cations to basidiomycete fungi. Environ. Toxicol. Chem. 2010;29:320-326. (C) 2009 SETAC

Financial time series analysis : Chaos and neurodynamics approach

This work aims at combining the Chaos theory postulates and Artificial Neural Networks classification and predictive capability, in the field of financial time series prediction. Chaos theory, provides valuable qualitative and quantitative tools to decide on the predictability of a chaotic system. Quantitative measurements based on Chaos theory, are used, to decide a-priori whether a time series, or a portion of a time series is predictable, while Chaos theory based qualitative tools are used to provide further observations and analysis on the predictability, in cases where measurements provide negative answers. Phase space reconstruction is achieved by time delay embedding resulting in multiple embedded vectors. The cognitive approach suggested, is inspired by the capability of some chartists to predict the direction of an index by looking at the price time series. Thus, in this work, the calculation of the embedding dimension and the separation, in Takens‘ embedding theorem for phase space reconstruction, is not limited to False Nearest Neighbor, Differential Entropy or other specific method, rather, this work is interested in all embedding dimensions and separations that are regarded as different ways of looking at a time series by different chartists, based on their expectations. Prior to the prediction, the embedded vectors of the phase space are classified with Fuzzy-ART, then, for each class a back propagation Neural Network is trained to predict the last element of each vector, whereas all previous elements of a vector are used as features.

Computational study of the step size parameter of the subgradient optimization method

The subgradient optimization method is a simple and flexible linear programming iterative algorithm. It is much simpler than Newton's method and can be applied to a wider variety of problems. It also converges when the objective function is non-differentiable. Since an efficient algorithm will not only produce a good solution but also take less computing time, we always prefer a simpler algorithm with high quality. In this study a series of step size parameters in the subgradient equation is studied. The performance is compared for a general piecewise function and a specific p-median problem. We examine how the quality of solution changes by setting five forms of step size parameter.

A Numerical method for the semilinear stochastic transport equation

Trabalho apresentado no XXXV CNMAC, Natal-RN, 2014.

A critical value function approach, with an application to persistent time-series

Researchers often rely on the t-statistic to make inference on parameters in statistical models. It is common practice to obtain critical values by simulation techniques. This paper proposes a novel numerical method to obtain an approximately similar test. This test rejects the null hypothesis when the test statistic islarger than a critical value function (CVF) of the data. We illustrate this procedure when regressors are highly persistent, a case in which commonly-used simulation methods encounter dificulties controlling size uniformly. Our approach works satisfactorily, controls size, and yields a test which outperforms the two other known similar tests.

Topliss method in the optimization of salicylic acid derivatives as potential antimycobacterial agents

The Topliss method was used to guide a synthetic path in support of drug discovery efforts toward the identification of potent antimycobacterial agents. Salicylic acid and its derivatives, p-chloro, p-methoxy, and m-chlorosalicylic acid, exemplify a series of synthetic compounds whose minimum inhibitory concentrations for a strain of Mycobacterium were determined and compared to those of the reference drug, p-aminosalicylic acid. Several physicochemical descriptors (including Hammett's sigma constant, ionization constant, dipole moment, Hansch constant, calculated partition coefficient, Sterimol-L and -B-4 and molecular volume) were considered to elucidate structure-activity relationships. Molecular electrostatic potential and molecular dipole moment maps were also calculated using the AM1 semi-empirical method. Among the new derivatives, m-chlorosalicylic acid showed the lowest minimum inhibitory concentration. The overall results suggest that both physicochemical properties and electronic features may influence the biological activity of this series of antimycobacterial agents and thus should be considered in designing new p-aminosalicylic acid analogs.

Zel'dovich's method of perturbation theory in quantum mechanics

Many years ago Zel'dovich showed how the Lagrange condition in the theory of differential equations can be utilized in the perturbation theory of quantum mechanics. Zel'dovich's method enables us to circumvent the summation over intermediate states. As compared with other similar methods, in particular the logarithmic perturbation expansion method, we emphasize that this relatively unknown method of Zel'dovich has a remarkable advantage in dealing with excited stares. That is, the ground and excited states can all be treated in the same way. The nodes of the unperturbed wavefunction do not give rise to any complication.

Studying nonlinear effects on the early stage of phase ordering using a decomposition method

Nonlinear effects on the early stage of phase ordering are studied using Adomian's decomposition method for the Ginzburg-Landau equation for a nonconserved order parameter. While the long-time regime and the linear behavior at short times of the theory are well understood, the onset of nonlinearities at short times and the breaking of the linear theory at different length scales are less understood. In the Adomians decomposition method, the solution is systematically calculated in the form of a polynomial expansion for the order parameter, with a time dependence given as a series expansion. The method is very accurate for short times, which allows to incorporate the short-time dynamics of the nonlinear terms in a analytical and controllable way. (c) 2005 Elsevier B.V. All rights reserved.

Remote sensing analysis of depositional landforms in alluvial settings: Method development and application to the Taquari megafan, Pantanal (Brazil)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Start-up of horizontal anaerobic reactors with sludge blanket and fixed bed for wastewater treatment from coffee processing by wet method

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)