876 resultados para nonparametric rationality tests


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Electrical road vehicles were common at the begin of the 20th century but internal combustion engines took a victory from electrical motors in road vehicles. The acknowledgement of the environment, and the price and the availability of the crude oil are reasons for the comeback of the electrical vehicles. Advancement in industrial technology and political atmosphere in EU as the directive 20--20--20, which consists of reducing fossil emission, increasing renewable energy and increasing the energy efficiency, have made the electrification popular again. In this thesis tests based on standard ISO 16750--2 electrical loads for electrical equipment in road vehicles are made for Visedo Oy's PowerMASTER M-frame power electronics device. This device is designed for mainly drive trains in mobile work machines and marine vessels but can be used in other application in its power range which also includes road vehicles. The functionality of the device is tested with preliminary tests which act as a framework for the tests based on standards.

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The effects oftwo types of small-group communication, synchronous computer-mediated and face-to-face, on the quantity and quality of verbal output were con^ared. Quantity was deiSned as the number of turns taken per minute, the number of Analysis-of-Speech units (AS-units) produced per minute, and the number ofwords produced per minute. Quality was defined as the number of words produced per AS-unit. In addition, the interaction of gender and type of communication was explored for any differences that existed in the output produced. Questionnaires were also given to participants to determine attitudes toward computer-mediated and face-to-face communication. Thirty intermediate-level students fi-om the Intensive English Language Program (lELP) at Brock University participated in the study, including 15 females and 15 males. Nonparametric tests, including the Wilcoxon matched-pairs test, Mann-Whitney U test, and Friedman test were used to test for significance at the p < .05 level. No significant differences were found in the effects of computer-mediated and face-to-face communication on the output produced during follow-up speaking sessions. However, the quantity and quality of interaction was significantly higher during face-to-face sessions than computer-mediated sessions. No significant differences were found in the output produced by males and females in these 2 conditions. While participants felt that the use of computer-mediated communication may aid in the development of certain language skills, they generally preferred face-to-face communication. These results differed fi-om previous studies that found a greater quantity and quality of output in addition to a greater equality of interaction produced during computer-mediated sessions in comparison to face-to-face sessions (Kern, 1995; Warschauer, 1996).

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The objective of this thesis is to demonstrate the importance of the concepts of rationality, reasonableness, culpability and autonomy that inform and support our conception of both the person and the punishable subject. A critical discourse analysis tracing these concepts through both the law and psychological tools used to evaluate the fitness of a person reveals that these concepts and their implied values are inconsistently applied to the mentally disordered who come into conflict with the law. I argue that the result of this inconsistency compromises a person's autonomy which is a contradiction to this concept as a foundational principle of the law. Ultimately, this thesis does not provide a solution to be employed in policy making, but its analysis leaves open possibilities for further exploration into the ways legal and social justice can be reconciled.

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This research evaluated (a) the correlation between math anxiety, math attitudes, and achievement in math and (b) comparison among these variables in terms of gender among grade 9 students in a high school located in southern Ontario. Data were compiled from participant responses to the Attitudes Toward Math Inventory (ATMI) and the Math Anxiety Rating Scale for Adolescents (MARS-A), and achievement data were gathered from participants’ grade 9 academic math course marks and the EQAO Grade 9 Assessment of Mathematics. Nonparametric tests were conducted to determine whether there were relationships between the variables and to explore whether gender differences in anxiety, attitudes, and achievement existed for this sample. Results indicated that math anxiety was not related to math achievement but was a strong correlate of attitudes toward math. A strong positive relationship was found between math attitudes and achievement in math. Specifically, self-confidence in math, enjoyment of math, value of math, and motivation were all positive correlates of achievement in math. Also, results for gender comparisons were nonsignificant, indicating that gender differences in math anxiety, math attitudes, and math achievement scores were not prevalent in this group of grade 9 students. Therefore, attitudes toward math were considered to be a stronger predictor of performance than math anxiety or gender for this group.

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The conclusion of the article states "it appears that previously learned choices may affect future choices in Y-mazes for cattle. Another area that needs to be researched is the effects of a mildly aversive treatment versus a severely aversive treatment on the tendency of a bovine to resist changing a learned choice".

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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.

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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.

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The focus of the paper is the nonparametric estimation of an instrumental regression function P defined by conditional moment restrictions stemming from a structural econometric model : E[Y-P(Z)|W]=0 and involving endogenous variables Y and Z and instruments W. The function P is the solution of an ill-posed inverse problem and we propose an estimation procedure based on Tikhonov regularization. The paper analyses identification and overidentification of this model and presents asymptotic properties of the estimated nonparametric instrumental regression function.

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Ce Texte Presente Plusieurs Resultats Exacts Sur les Seconds Moments des Autocorrelations Echantillonnales, Pour des Series Gaussiennes Ou Non-Gaussiennes. Nous Donnons D'abord des Formules Generales Pour la Moyenne, la Variance et les Covariances des Autocorrelations Echantillonnales, Dans le Cas Ou les Variables de la Serie Sont Interchangeables. Nous Deduisons de Celles-Ci des Bornes Pour les Variances et les Covariances des Autocorrelations Echantillonnales. Ces Bornes Sont Utilisees Pour Obtenir des Limites Exactes Sur les Points Critiques Lorsqu'on Teste le Caractere Aleatoire D'une Serie Chronologique, Sans Qu'aucune Hypothese Soit Necessaire Sur la Forme de la Distribution Sous-Jacente. Nous Donnons des Formules Exactes et Explicites Pour les Variances et Covariances des Autocorrelations Dans le Cas Ou la Serie Est un Bruit Blanc Gaussien. Nous Montrons Que Ces Resultats Sont Aussi Valides Lorsque la Distribution de la Serie Est Spheriquement Symetrique. Nous Presentons les Resultats D'une Simulation Qui Indiquent Clairement Qu'on Approxime Beaucoup Mieux la Distribution des Autocorrelations Echantillonnales En Normalisant Celles-Ci Avec la Moyenne et la Variance Exactes et En Utilisant la Loi N(0,1) Asymptotique, Plutot Qu'en Employant les Seconds Moments Approximatifs Couramment En Usage. Nous Etudions Aussi les Variances et Covariances Exactes D'autocorrelations Basees Sur les Rangs des Observations.

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This Paper Studies Tests of Joint Hypotheses in Time Series Regression with a Unit Root in Which Weakly Dependent and Heterogeneously Distributed Innovations Are Allowed. We Consider Two Types of Regression: One with a Constant and Lagged Dependent Variable, and the Other with a Trend Added. the Statistics Studied Are the Regression \"F-Test\" Originally Analysed by Dickey and Fuller (1981) in a Less General Framework. the Limiting Distributions Are Found Using Functinal Central Limit Theory. New Test Statistics Are Proposed Which Require Only Already Tabulated Critical Values But Which Are Valid in a Quite General Framework (Including Finite Order Arma Models Generated by Gaussian Errors). This Study Extends the Results on Single Coefficients Derived in Phillips (1986A) and Phillips and Perron (1986).

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In This Paper Several Additional Gmm Specification Tests Are Studied. a First Test Is a Chow-Type Test for Structural Parameter Stability of Gmm Estimates. the Test Is Inspired by the Fact That \"Taste and Technology\" Parameters Are Uncovered. the Second Set of Specification Tests Are Var Encompassing Tests. It Is Assumed That the Dgp Has a Finite Var Representation. the Moment Restrictions Which Are Suggested by Economic Theory and Exploited in the Gmm Procedure Represent One Possible Characterization of the Dgp. the Var Is a Different But Compatible Characterization of the Same Dgp. the Idea of the Var Encompassing Tests Is to Compare Parameter Estimates of the Euler Conditions and Var Representations of the Dgp Obtained Separately with Parameter Estimates of the Euler Conditions and Var Representations Obtained Jointly. There Are Several Ways to Construct Joint Systems Which Are Discussed in the Paper. Several Applications Are Also Discussed.

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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.

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We extend the class of M-tests for a unit root analyzed by Perron and Ng (1996) and Ng and Perron (1997) to the case where a change in the trend function is allowed to occur at an unknown time. These tests M(GLS) adopt the GLS detrending approach of Dufour and King (1991) and Elliott, Rothenberg and Stock (1996) (ERS). Following Perron (1989), we consider two models : one allowing for a change in slope and the other for both a change in intercept and slope. We derive the asymptotic distribution of the tests as well as that of the feasible point optimal tests PT(GLS) suggested by ERS. The asymptotic critical values of the tests are tabulated. Also, we compute the non-centrality parameter used for the local GLS detrending that permits the tests to have 50% asymptotic power at that value. We show that the M(GLS) and PT(GLS) tests have an asymptotic power function close to the power envelope. An extensive simulation study analyzes the size and power in finite samples under various methods to select the truncation lag for the autoregressive spectral density estimator. An empirical application is also provided.

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In the literature on tests of normality, much concern has been expressed over the problems associated with residual-based procedures. Indeed, the specialized tables of critical points which are needed to perform the tests have been derived for the location-scale model; hence reliance on available significance points in the context of regression models may cause size distortions. We propose a general solution to the problem of controlling the size normality tests for the disturbances of standard linear regression, which is based on using the technique of Monte Carlo tests.