Mesures de flux de cadmium dans un sol contaminé par la méthode du DGT

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Méthode proposant l'utilisation de la programmation fonctionnelle pour la génération de solutions architecturales partielles sous forme matricielle

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Méthode structurelle pour le suivi automatique des artères coronaires en ciné-angiographie

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

À la recherche des mots perdus : essai sur la méthode en histoire (Arendt, de Certeau, Foucault)

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Analyse critique du contenu linguistique de la méthode New Interchange en anglais L2

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Mise au point d'une méthode de culture tissulaire pour l'évaluation de l'effet antiangiogène de quelques substances

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Développement d'un système de monitorage du blocage neuromusculaire par la méthode de phonomyographie

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Développement d'une méthode accélérométrique tridimensionnelle pour l'évaluation d'une population atteinte d'arthrose du genou : application à un contexte de marche

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Méthode d'étude moléculaire des tumeurs rares pédiatriques = Methods of molecular analysis to study rare paediatric tumours

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Analyse comparative de l’approche bioclimatique et de la méthode LEED en architecture

Motivé par l’évolution de la production architecturale durable dans les pays d’Amérique latine, et plus particulièrement en Colombie, mon projet de recherche porte sur l’adaptation de l’architecture à ce nouveau contexte. L’approche architecturale traditionnelle à la prise en compte de l’énergie et du climat est l’architecture bioclimatique : reproduite à partir de connaissances et techniques ancestrales remontant à la conception de l’abri, cette dernière étudie les phénomènes physiques associés au confort thermique afin de les reproduire dans une nouvelle architecture. De nouvelles méthodes d’évaluation environnementale se sont développées dans les dernières décennies pour améliorer l’intégration environnementale des bâtiments. Ces méthodes privilégient la normalisation des solutions et utilisent des systèmes de certification pour reconnaître la performance environnementale et énergétique des bâtiments. Le résultat visé est la conformité aux standards internationaux de durabilité. Ce mémoire porte sur l’analyse comparative de l’architecture bioclimatique et de la certification environnementale à partir de la structure des sujets abordés par LEED, une des méthodes les plus connues d’une telle certification. Cette comparaison permet de constater que les deux approches sont motivées par les mêmes préoccupations environnementales mais que leurs méthodes d’intégration de ces préoccupations diffèrent, en particulier quant à la prise en compte des facteurs locaux et globaux.

International Business Cycles: What Are the Facts?

Modern business cycle theory involves developing models that explain stylized facts. For this strategy to be successful, these facts should be well established. In this paper, we focus on the stylized facts of international business cycles. We use the generalized method of moments and quarterly data from nineteen industrialized countries to estimate pairwise cross-country and within-country correlations of macroeconomic aggregates. We calculate standard errors of the statistics for our unique panel of data and test hypotheses about the relative sizes of these correlations. We find a lower cross-country correlation of all aggregates and especially of consumption than in previous studies. The cross-country correlations of consumption, output and Solow residuals are not significantly different from one another over the whole sample, but there are significant differences in the post-1973 subsample.

Simulation-Based Finite and Large Sample Tests in Multivariate Regressions.

In the context of multivariate linear regression (MLR) models, it is well known that commonly employed asymptotic test criteria are seriously biased towards overrejection. In this paper, we propose a general method for constructing exact tests of possibly nonlinear hypotheses on the coefficients of MLR systems. For the case of uniform linear hypotheses, we present exact distributional invariance results concerning several standard test criteria. These include Wilks' likelihood ratio (LR) criterion as well as trace and maximum root criteria. The normality assumption is not necessary for most of the results to hold. Implications for inference are two-fold. First, invariance to nuisance parameters entails that the technique of Monte Carlo tests can be applied on all these statistics to obtain exact tests of uniform linear hypotheses. Second, the invariance property of the latter statistic is exploited to derive general nuisance-parameter-free bounds on the distribution of the LR statistic for arbitrary hypotheses. Even though it may be difficult to compute these bounds analytically, they can easily be simulated, hence yielding exact bounds Monte Carlo tests. Illustrative simulation experiments show that the bounds are sufficiently tight to provide conclusive results with a high probability. Our findings illustrate the value of the bounds as a tool to be used in conjunction with more traditional simulation-based test methods (e.g., the parametric bootstrap) which may be applied when the bounds are not conclusive.

Exact Tests for Contemporaneous Correlation of Disturbances in Seemingly Unrelated Regressions.

This paper proposes finite-sample procedures for testing the SURE specification in multi-equation regression models, i.e. whether the disturbances in different equations are contemporaneously uncorrelated or not. We apply the technique of Monte Carlo (MC) tests [Dwass (1957), Barnard (1963)] to obtain exact tests based on standard LR and LM zero correlation tests. We also suggest a MC quasi-LR (QLR) test based on feasible generalized least squares (FGLS). We show that the latter statistics are pivotal under the null, which provides the justification for applying MC tests. Furthermore, we extend the exact independence test proposed by Harvey and Phillips (1982) to the multi-equation framework. Specifically, we introduce several induced tests based on a set of simultaneous Harvey/Phillips-type tests and suggest a simulation-based solution to the associated combination problem. The properties of the proposed tests are studied in a Monte Carlo experiment which shows that standard asymptotic tests exhibit important size distortions, while MC tests achieve complete size control and display good power. Moreover, MC-QLR tests performed best in terms of power, a result of interest from the point of view of simulation-based tests. The power of the MC induced tests improves appreciably in comparison to standard Bonferroni tests and, in certain cases, outperforms the likelihood-based MC tests. The tests are applied to data used by Fischer (1993) to analyze the macroeconomic determinants of growth.

Markovian Processes, Two-Sided Autoregressions and Finite-Sample Inference for Stationary and Nonstationary Autoregressive Processes.

In this paper, we develop finite-sample inference procedures for stationary and nonstationary autoregressive (AR) models. The method is based on special properties of Markov processes and a split-sample technique. The results on Markovian processes (intercalary independence and truncation) only require the existence of conditional densities. They are proved for possibly nonstationary and/or non-Gaussian multivariate Markov processes. In the context of a linear regression model with AR(1) errors, we show how these results can be used to simplify the distributional properties of the model by conditioning a subset of the data on the remaining observations. This transformation leads to a new model which has the form of a two-sided autoregression to which standard classical linear regression inference techniques can be applied. We show how to derive tests and confidence sets for the mean and/or autoregressive parameters of the model. We also develop a test on the order of an autoregression. We show that a combination of subsample-based inferences can improve the performance of the procedure. An application to U.S. domestic investment data illustrates the method.