代數學Dai shu xue.De Morgan's Algebra.

Traduction Chinoise par Alexander Wylie (1815-1887), rédigée par Li Shan lan, de Hai ning. Préface Chinoise par Wylie (1859) ; préface anglaise, écrite par le même à Shang hai (octobre 1859), contenant un historique des mathématiques en Chine. Imprimé en caractères mobiles, dans la maison Mo hai (1859).Livre préliminaire + 13 livres.

代微積拾級Dai wei ji shi ji.Loomis' Analytical Geometry and Differential and Integral Calculus.

Traduction de Wylie, rédigée par Li Shan lan ; préfaces Chinoises des deux traducteurs (1859) ; préface anglaise, écrite à Shang hai par A. Wylie (juillet 1859). Liste de termes techniques en anglais et en Chinois. Gravé à la maison Mo hai (1859).18 livres.

Supplément grec 1295

PORSON (Richard). papiers

Collection des observations...

Comprend : Observations pratiques publiées par la "Revue du notariat" jusqu'au 1er janvier 1869

Collection des observations...

Comprend : Observations pratiques publiées par la "Revue du notariat" jusqu'au 1er janvier 1869

Les services de référence en milieu universitaire : de nouvelles orientations!

Communication présentée dans le cadre du programme de formation continue de la Corporation des bibliothécaires professionnels du Québec, vendredi le 11 mars 2005.

L’avenir des services de référence des bibliothèques universitaires

Le texte qui suit présente d’abord une « petite histoire de la référence », une rétrospective des pratiques de services de référence dans les bibliothèques universitaires depuis les années 1970, et ce à partir de l’expérience des bibliothèques universitaires de l’Université de Montréal. Par la suite, les auteurs font une analyse de l’impact des nouvelles technologies sur les services de référence à une époque de rationalisation du travail et de coupures de personnel. Une réflexion est ensuite proposée sur ce que sera l’avenir des professionnels de la référence dans un contexte de travail plus exigeant marqué par l’augmentation de la charge de travail, l’importance de plus en plus grande des qualités pédagogiques et la spécialisation des tâches, sans oublier le fait que le bibliothécaire de référence, en bâtissant des collections et des portails dans sa discipline de spécialisation, deviendra sans doute de plus en plus un gestionnaire de l’information.

La syndication de contenu (fils RSS) en bibliothèque

Présenté au personnel de la Direction des bibliothèques lors d'une conférence-midi le 8 mars 2006.

The Seemingly Unrelated Dynamic Cointegration Regression Model and Testing for Purching Power Parity.

This paper studies seemingly unrelated linear models with integrated regressors and stationary errors. By adding leads and lags of the first differences of the regressors and estimating this augmented dynamic regression model by feasible generalized least squares using the long-run covariance matrix, we obtain an efficient estimator of the cointegrating vector that has a limiting mixed normal distribution. Simulation results suggest that this new estimator compares favorably with others already proposed in the literature. We apply these new estimators to the testing of purchasing power parity (PPP) among the G-7 countries. The test based on the efficient estimates rejects the PPP hypothesis for most countries.

Sharing a River

A group of agents located along a river have quasi-linear preferences over water and money. We ask how the water should be allocated and what money transfers should be performed. We are interested in efficiency, stability (in the sense of the core), and fairness (in a sense to be defined). We first show that the cooperative game associated with our problem is convex : its core is therefore large and easily described. Next, we propose the following fairness requirement : no group of agents should enjoy a welfare higher than what it could achieve in the absence of the remaining agents. We prove that only one welfare vector in the core satisfies this condition : it is the marginal contribution vector corresponding to the ordering of the agents along the river. We discuss how it could be decentralized or implemented.

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.