Chaotic systems with a null conditional Lyapunov exponent under nonlinear driving.

Control of a chaotic system by homogeneous nonlinear driving, when a conditional Lyapunov exponent is zero, may give rise to special and interesting synchronizationlike behaviors in which the response evolves in perfect correlation with the drive. Among them, there are the amplification of the drive attractor and the shift of it to a different region of phase space. In this paper, these synchronizationlike behaviors are discussed, and demonstrated by computer simulation of the Lorentz model [E. N. Lorenz, J. Atmos. Sci. 20 130 (1963)] and the double scroll [T. Matsumoto, L. O. Chua, and M. Komuro, IEEE Trans. CAS CAS-32, 798 (1985)].

Conditional maximum likelihood timing recovery: estimators and bounds

This paper is concerned with the derivation of new estimators and performance bounds for the problem of timing estimation of (linearly) digitally modulated signals. The conditional maximum likelihood (CML) method is adopted, in contrast to the classical low-SNR unconditional ML (UML) formulationthat is systematically applied in the literature for the derivationof non-data-aided (NDA) timing-error-detectors (TEDs). A new CML TED is derived and proved to be self-noise free, in contrast to the conventional low-SNR-UML TED. In addition, the paper provides a derivation of the conditional Cramér–Rao Bound (CRB ), which is higher (less optimistic) than the modified CRB (MCRB)[which is only reached by decision-directed (DD) methods]. It is shown that the CRB is a lower bound on the asymptotic statisticalaccuracy of the set of consistent estimators that are quadratic with respect to the received signal. Although the obtained boundis not general, it applies to most NDA synchronizers proposed in the literature. A closed-form expression of the conditional CRBis obtained, and numerical results confirm that the CML TED attains the new bound for moderate to high Eg/No.

Alternative tests for correct specification of conditional predictive densities

We propose new methods for evaluating predictive densities that focus on the models' actual predictive ability in finite samples. The tests offer a simple way of evaluatingthe correct specification of predictive densities, either parametric or non-parametric.The results indicate that our tests are well sized and have good power in detecting mis-specification in predictive densities. An empirical application to the Survey ofProfessional Forecasters and a baseline Dynamic Stochastic General Equilibrium modelshows the usefulness of our methodology.

Conditional equilibrium constants in multicomponent heterogeneous adsorption: The conditional affinity spectrum

The concept of conditional stability constant is extended to the competitive binding of small molecules to heterogeneous surfaces or macromolecules via the introduction of the conditional affinity spectrum (CAS). The CAS describes the distribution of effective binding energies experienced by one complexing agent at a fixed concentration of the rest. We show that, when the multicomponent system can be described in terms of an underlying affinity spectrum [integral equation (IE) approach], the system can always be characterized by means of a CAS. The thermodynamic properties of the CAS and its dependence on the concentration of the rest of components are discussed. In the context of metal/proton competition, analytical expressions for the mean (conditional average affinity) and the variance (conditional heterogeneity) of the CAS as functions of pH are reported and their physical interpretation discussed. Furthermore, we show that the dependence of the CAS variance on pH allows for the analytical determination of the correlation coefficient between the binding energies of the metal and the proton. Nonideal competitive adsorption isotherm and Frumkin isotherms are used to illustrate the results of this work. Finally, the possibility of using CAS when the IE approach does not apply (for instance, when multidentate binding is present) is explored. © 2006 American Institute of Physics.

Measuring school demand in the presence of spatial dependence. A conditional approach

Improving educational quality is an important public policy goal. However, its success requires identifying factors associated with student achievement. At the core of these proposals lies the principle that increased public school quality can make school system more efficient, resulting in correspondingly stronger performance by students. Nevertheless, the public educational system is not devoid of competition which arises, among other factors, through the efficiency of management and the geographical location of schools. Moreover, families in Spain appear to choose a school on the grounds of location. In this environment, the objective of this paper is to analyze whether geographical space has an impact on the relationship between the level of technical quality of public schools (measured by the efficiency score) and the school demand index. To do this, an empirical application is performed on a sample of 1,695 public schools in the region of Catalonia (Spain). This application shows the effects of spatial autocorrelation on the estimation of the parameters and how these problems are addressed through spatial econometrics models. The results confirm that space has a moderating effect on the relationship between efficiency and school demand, although only in urban municipalities.

Time-varying Risk Premiums and Conditional Market Risk: Empirical Evidence from European Stock Markets

This study investigates the relationship between the time-varying risk premiums and conditional market risk in the stock markets of the ten member countries of Economy and Monetary Union. Second, it examines whether the conditional second moments change over time and are there asymmetric effects in the conditional covariance matrix. Third, it analyzes the possible effects of the chosen testing framework. Empirical analysis is conducted using asymmetric univariate and multivariate GARCH-in-mean models and assuming three different degrees of market integration. For a daily sample period from 1999 to 2007, the study shows that the time-varying market risk alone is not enough to explain the dynamics of risk premiums and indications are found that the market risk is detected only when its price is allowed to change over time. Also asymmetric effects in the conditional covariance matrix, which is found to be time-varying, are clearly present and should be recognized in empirical asset pricing analyses.

Contact with friction using the augmented Lagrangian Method: a conditional constrained minimization problem

This work presents a formulation of the contact with friction between elastic bodies. This is a non linear problem due to unilateral constraints (inter-penetration of bodies) and friction. The solution of this problem can be found using optimization concepts, modelling the problem as a constrained minimization problem. The Finite Element Method is used to construct approximation spaces. The minimization problem has the total potential energy of the elastic bodies as the objective function, the non-inter-penetration conditions are represented by inequality constraints, and equality constraints are used to deal with the friction. Due to the presence of two friction conditions (stick and slip), specific equality constraints are present or not according to the current condition. Since the Coulomb friction condition depends on the normal and tangential contact stresses related to the constraints of the problem, it is devised a conditional dependent constrained minimization problem. An Augmented Lagrangian Method for constrained minimization is employed to solve this problem. This method, when applied to a contact problem, presents Lagrange Multipliers which have the physical meaning of contact forces. This fact allows to check the friction condition at each iteration. These concepts make possible to devise a computational scheme which lead to good numerical results.

Comparison of Pavlovian serial conditional discrimination in rats and hamsters in the same experimental situation

The present study compares behavioral changes between two distinct rodent groups, hamsters (Mesocricetus auratus) and Wistar rats, when submitted in the same homogeneous experimental situations to a serial conditional discrimination procedure which involves water deprivation and the processing of temporal variables. Both hamsters and rats acquired serial positive conditional discrimination as indicated by higher frequencies of magazine-oriented behavior during the tone followed by reinforcement (T+) and preceded by the feature stimulus light (L) and during the empty interval, than during the tone alone not followed by reinforcement (T-). Rats' frequencies of magazine-oriented behavior were high during T+ and T-, initially during training, and decreased during T- as the training progressed. However, the hamsters' frequencies of magazine-oriented behavior started very low and increased only during T+ as the training progressed. Comparison of the frequencies of magazine-oriented behavior during the empty interval in relation to the frequencies during the preceding L period showed that rats' frequencies remained very high and hamsters' frequencies increased during training. These results suggest that rats and hamsters have different behavioral strategies for the acquisition of a conditional discrimination. The results of the comparisons made in these experiments support the view of the importance of an ecological psychology approach to the understanding of complex learning in animals.

Time Varying Conditional Correlation Between Stock And Bond Returns: Evidence From CIVETS Nations

This thesis estimates long-run time variant conditional correlation between stock and bond returns of CIVETS (Colombia, Indonesia, Vietnam, Egypt, Turkey, and South Africa) nations. Further, aims to analyse the presence of asymmetric volatility effect in both asset returns, as well as, obverses increment or decrement in conditional correlation during pre-crisis and crisis period, which lead to make a reliable diversification decision. The Constant Conditional Correlation (CCC) GARCH model of Bollerslev (1990), the Dynamic Conditional Correlation (DCC) GARCH model (Engle 2002), and the Asymmetric Dynamic Conditional Correlation (ADCC) GARCH model of Cappiello, Engle, and Sheppard (2006) were implemented in the study. The analyses present strong evidence of time-varying conditional correlation in CIVETS markets, excluding Vietnam, during 2005-2013. In addition, negative innovation effects were found in both conditional variance and correlation of the asset returns. The results of this study recommend investors to include financial assets from these markets in portfolios, in order to obtain better stock-bond diversification benefits, especially during high volatility periods.

Russian and Eastern European Dynamic Conditional Correlations in light of the Russian crisis of 2014-2015

This thesis studies the impact of the latest Russian crisis on global markets, and especially Central and Eastern Europe. The results are compared to other shocks and crises over the last twenty years to see how significant they have been. The cointegration process of Central and Eastern European financial markets is also reviewed and updated. Using three separate conditional correlation GARCH models, the latest crisis is not found to have initiated similar surges in conditional correlations to previous crises over the last two decades. Market cointegration for Central and Eastern Europe is found to have stalled somewhat after initial correlation increases post EU accession.

Operant serial feature-positive conditional discrimination with composite features and different topography responses

In a serial feature-positive conditional discrimination procedure the properties of a target stimulus A are defined by the presence or not of a feature stimulus X preceding it. In the present experiment, composite features preceded targets associated with two different topography operant responses (right and left bar pressing); matching and non-matching-to-sample arrangements were also used. Five water-deprived Wistar rats were trained in 6 different trials: X-R®Ar and X-L®Al, in which X and A were same modality visual stimuli and the reinforcement was contingent to pressing either the right (r) or left (l) bar that had the light on during the feature (matching-to-sample); Y-R®Bl and Y-L®Br, in which Y and B were same modality auditory stimuli and the reinforcement was contingent to pressing the bar that had the light off during the feature (non-matching-to-sample); A- and B- alone. After 100 training sessions, the animals were submitted to transfer tests with the targets used plus a new one (auditory click). Average percentages of stimuli with a response were measured. Acquisition occurred completely only for Y-L®Br+; however, complex associations were established along training. Transfer was not complete during the tests since concurrent effects of extinction and response generalization also occurred. Results suggest the use of both simple conditioning and configurational strategies, favoring the most recent theories of conditional discrimination learning. The implications of the use of complex arrangements for discussing these theories are considered.

Tests of Conditional Asset Pricing Models in the Brazilian Stock Market

In this paper, we test a version of the conditional CAPM with respect to a local market portfolio, proxied by the Brazilian stock index during the 1976-1992 period. We also test a conditional APT model by using the difference between the 30-day rate (Cdb) and the overnight rate as a second factor in addition to the market portfolio in order to capture the large inflation risk present during this period. The conditional CAPM and APT models are estimated by the Generalized Method of Moments (GMM) and tested on a set of size portfolios created from a total of 25 securities exchanged on the Brazilian markets. The inclusion of this second factor proves to be crucial for the appropriate pricing of the portfolios.