On the finite-sample properties of conditional empirical likelihood estimators

We provide Monte Carlo evidence on the finite sample behavior of the conditional empirical likelihood (CEL) estimator of Kitamura, Tripathi, and Ahn (2004) and the conditional Euclidean empirical likelihood (CEEL) estimator of Antoine, Bonnal, and Renault (2007) in the context of a heteroskedastic linear model with an endogenous regressor. We compare these estimators with three heteroskedasticity-consistent instrument-based estimators in terms of various performance measures. Our results suggest that the CEL and CEEL with fixed bandwidths may suffer from the no-moment problem, similarly to the unconditional generalized empirical likelihood estimators studied by Guggenberger (2008). We also study the CEL and CEEL estimators with automatic bandwidths selected through cross-validation. We do not find evidence that these suffer from the no-moment problem. When the instruments are weak, we find CEL and CEEL to have finite sample properties --in terms of mean squared error and coverage probability of confidence intervals-- poorer than the heteroskedasticity-consistent Fuller (HFUL) estimator. In the strong instruments case the CEL and CEEL estimators with automatic bandwidths tend to outperform HFUL in terms of mean squared error, while the reverse holds in terms of the coverage probability, although the differences in numerical performance are rather small.Conditional empirical likelihood; conditional Euclidean likelihood; heteroskedasticity; weak instruments; cross-validation

On the Finite Sample Properties of Conditional Empirical Likelihood Estimators

We provide Monte Carlo evidence on the finite-sample behavior of the conditional empirical likelihood (CEL) estimator of Kitamura, Tripathi, and Ahn and the conditional Euclidean empirical likelihood (CEEL) estimator of Antoine, Bonnal, and Renault in the context of a heteroscedastic linear model with an endogenous regressor. We compare these estimators with three heteroscedasticity-consistent instrument-based estimators and the Donald, Imbens, and Newey estimator in terms of various performance measures. Our results suggest that the CEL and CEEL with fixed bandwidths may suffer from the no-moment problem, similarly to the unconditional generalized empirical likelihood estimators studied by Guggenberger. We also study the CEL and CEEL estimators with automatic bandwidths selected through cross-validation. We do not find evidence that these suffer from the no-moment problem. When the instruments are weak, we find CEL and CEEL to have finite-sample properties—in terms of mean squared error and coverage probability of confidence intervals—poorer than the heteroscedasticity-consistent Fuller (HFUL) estimator. In the strong instruments case, the CEL and CEEL estimators with automatic bandwidths tend to outperform HFUL in terms of mean squared error, while the reverse holds in terms of the coverage probability, although the differences in numerical performance are rather small

Bilinear form test statistics for extremum estimation

This paper develops a set of test statistics based on bilinear forms in the context of the extremum estimation framework with particular interest in nonlinear hypothesis. We show that the proposed statistic converges to a conventional chi-square limit. A Monte Carlo experiment suggests that the test statistic works well in finite samples.Comment: 6 pages, 12 figure

Hybrid stochastic simplifications for multiscale gene networks

<p>Abstract</p> <p>Background</p> <p>Stochastic simulation of gene networks by Markov processes has important applications in molecular biology. The complexity of exact simulation algorithms scales with the number of discrete jumps to be performed. Approximate schemes reduce the computational time by reducing the number of simulated discrete events. Also, answering important questions about the relation between network topology and intrinsic noise generation and propagation should be based on general mathematical results. These general results are difficult to obtain for exact models.</p> <p>Results</p> <p>We propose a unified framework for hybrid simplifications of Markov models of multiscale stochastic gene networks dynamics. We discuss several possible hybrid simplifications, and provide algorithms to obtain them from pure jump processes. In hybrid simplifications, some components are discrete and evolve by jumps, while other components are continuous. Hybrid simplifications are obtained by partial Kramers-Moyal expansion <abbrgrp><abbr bid="B1">1</abbr><abbr bid="B2">2</abbr><abbr bid="B3">3</abbr></abbrgrp> which is equivalent to the application of the central limit theorem to a sub-model. By averaging and variable aggregation we drastically reduce simulation time and eliminate non-critical reactions. Hybrid and averaged simplifications can be used for more effective simulation algorithms and for obtaining general design principles relating noise to topology and time scales. The simplified models reproduce with good accuracy the stochastic properties of the gene networks, including waiting times in intermittence phenomena, fluctuation amplitudes and stationary distributions. The methods are illustrated on several gene network examples.</p> <p>Conclusion</p> <p>Hybrid simplifications can be used for onion-like (multi-layered) approaches to multi-scale biochemical systems, in which various descriptions are used at various scales. Sets of discrete and continuous variables are treated with different methods and are coupled together in a physically justified approach.</p

Errors-in-Variables Models with Many Proxies

This paper introduces a novel method to estimate linear models when explanatory variables are observed with error and many proxies are available. The empirical Euclidean likelihood principle is used to combine the information that comes from the various mismeasured variables. We show that the proposed estimator is consistent and asymptotically normal. In a Monte Carlo study we show that our method is able to efficiently use the information in the available proxies, both in terms of precision of the estimator and in terms of statistical power. An application to the effect of police on crime suggests that measurement errors in the police variable induce substantial attenuation bias. Our approach, on the other hand, yields large estimates in absolute value with high precision, in accordance with the results put forward by the recent literature

Rolul stresului oxidativ în declanșarea bolilor autoimune

Background. Autoimmune diseases include a heterogeneous group of disorders associated with loss of immunological tolerance to autoantigens. These are the result of complex reaction, with the involvement of triggers that induce a certain degree of oxidative stress, which directly affects the immune cells. Objective of the study. Analysis and understanding of the role of oxidative stress in triggering a number of autoimmune diseases such as rheumatoid arthritis, systemic lupus erythematosus, etc. Material and Methods. The literature review was developed based on the analysis of contemporary specialized scientific information. Results. Oxidative stress is an effect of the redox imbalance between reactive oxygen species (ROS) and antioxidant defense, with oxidizing species primarily including free radicals (FR). The two main families of oxidants relevant in biology are reactive oxygen species (ROS) and reactive nitrogen species (RNS). Under physiological conditions, the defenses counterbalance the production of ROS and RNS, but in conditions of excessive production or if the body’s defenses are compromised, ROS and RNS can react with fatty acids, causing proteins and DNA to damage these substrates. Conclusion. This review demonstrates the close relationship between oxidative stress and the onset of autoimmune diseases. ROS overproduction will cause oxidation of proteins, lipids, change of DNA bases and breakage of the chain or even lead to cell damage.Introducere. Bolile autoimune regrupează un grup eterogen de tulburări asociate cu pierderea toleranței imunologice la autoantigene. Ele se dezvoltă pe fundaluri complexe, cu implicarea unor factori declanșatori ce induc un anumit grad de stres oxidativ care afectează direct celulele imune. Scopul lucrării. Analiza și înțelegerea rolului stresului oxidativ în declanșarea unui șir de boli autoimune ca artrita reumatoidă, lupusul eritematos sistemic, etc. Material și metode. Review-ul de literatură a fost elaborat în baza analizei informației științifice contemporane de specialitate. Rezultate. Stresul oxidativ reprezintă un efect al dezechilibrului redox între speciile reactive de oxigen (SRO) și apărarea antioxidantă, speciile oxidante incluzând în primul rând radicalii liberi (RL). Cele două familii principale de oxidanți relevanți în biologie sunt speciile reactive de oxigen (SRO) și speciile reactive de azot (SRN). În condiții fiziologice, căile de apărare contrabalansează producția de ROS și RNS, însă în condiții de producție excesivă sau în cazul în care apărările corpului sunt compromise, SRO și SRN pot reacționa cu acizii grași, proteinele și ADN-ul provocând astfel deteriorarea acestor substraturi. Concluzii. Review-ul dat demonstrează existența unei relații strânse între stresul oxidativ și declanșarea bolilor autoimune. Supraproducția SRO va cauza oxidarea proteinelor, lipidelor, schimbarea bazelor ADN-ului și rupturi ale catenei sau chiar va duce la lezarea celulelor

Blockwise Euclidean likelihood for spatio-temporal covariance models

A spatio-temporal blockwise Euclidean likelihood method for the estimation of covariance models when dealing with large spatio-temporal Gaussian data is proposed. The method uses moment conditions coming from the score of the pairwise composite likelihood. The blockwise approach guarantees considerable computational improvements over the standard pairwise composite likelihood method. In order to further speed up computation, a general purpose graphics processing unit implementation using OpenCL is implemented. The asymptotic properties of the proposed estimator are derived and the finite sample properties of this methodology by means of a simulation study highlighting the computational gains of the OpenCL graphics processing unit implementation. Finally, there is an application of the estimation method to a wind component data set

THE ROLE OF OXIDATIVE STRESS IN THE TRIGGERING OF AUTOIMMUNE DISEASES

Universitatea de Stat de Medicină şi Farmacie „Nicolae Testemiţanu”, Chişinău, Republica MoldovaIntroducere. Bolile autoimune regrupează un grup eterogen de tulburări asociate cu pierderea toleranței imunologice la autoantigene. Ele se dezvoltă pe fundaluri complexe, cu implicarea unor factori declanșatori ce induc un anumit grad de stres oxidativ care afectează direct celulele imune. Scopul lucrării. Analiza și înțelegerea rolului stresului oxidativ în declanșarea unui șir de boli autoimune ca artrita reumatoidă, lupusul eritematos sistemic, etc. Material și metode. Review-ul de literatură a fost elaborat în baza analizei informației științifice contemporane de specialitate. Rezultate. Stresul oxidativ reprezintă un efect al dezechilibrului redox între speciile reactive de oxigen (SRO) și apărarea antioxidantă, speciile oxidante incluzând în primul rând radicalii liberi (RL). Cele două familii principale de oxidanți relevanți în biologie sunt speciile reactive de oxigen (SRO) și speciile reactive de azot (SRN). În condiții fiziologice, căile de apărare contrabalansează producția de ROS și RNS, însă în condiții de producție excesivă sau în cazul în care apărările corpului sunt compromise, SRO și SRN pot reacționa cu acizii grași, proteinele și ADN-ul provocând astfel deteriorarea acestor substraturi. Concluzii. Review-ul dat demonstrează existența unei relații strânse între stresul oxidativ și declanșarea bolilor autoimune. Supraproducția SRO va cauza oxidarea proteinelor, lipidelor, schimbarea bazelor ADN-ului și rupturi ale catenei sau chiar va duce la lezarea celulelor.Background. Autoimmune diseases include a heterogeneous group of disorders associated with loss of immunological tolerance to autoantigens. These are the result of complex reaction, with the involvement of triggers that induce a certain degree of oxidative stress, which directly affects the immune cells. Objective of the study. Analysis and understanding of the role of oxidative stress in triggering a number of autoimmune diseases such as rheumatoid arthritis, systemic lupus erythematosus, etc. Material and Methods. The literature review was developed based on the analysis of contemporary specialized scientific information. Results. Oxidative stress is an effect of the redox imbalance between reactive oxygen species (ROS) and antioxidant defense, with oxidizing species primarily including free radicals (FR). The two main families of oxidants relevant in biology are reactive oxygen species (ROS) and reactive nitrogen species (RNS). Under physiological conditions, the defenses counterbalance the production of ROS and RNS, but in conditions of excessive production or if the body’s defenses are compromised, ROS and RNS can react with fatty acids, causing proteins and DNA to damage these substrates. Conclusion. This review demonstrates the close relationship between oxidative stress and the onset of autoimmune diseases. ROS overproduction will cause oxidation of proteins, lipids, change of DNA bases and breakage of the chain or even lead to cell damage

THE DEVELOPMENT OF THE SICENTIFIC RESEARCHES IN THE EUROPEAN UNION. CASE STUDY, FRANCE

The agricultural scientific research institutions constitute the vertebral tier of the world system. Eitheir the research institutions are under the national agricultural form, or they are under the form of agricultural research councils, that act as coordination bodies of the regional or local specialized research institutions, that form the biggest part of the research capacities in each region of the world. In the present study, I chose France because it has an agricultural surface of almost 30 million hectares, that represents more than a half of the total surface of its territory. The lands situated on one side and on the other side of 45 North latitude paralel allow a large variety of production. About 61% of the agricultural surface of the country is occupied with crops, 35% pastures and 4% vineyards. The paper makes an analysis of the research in the agricultural sector, in France and it highlights its main positive particularities, that apply also in other European Union countries