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Pierre Duchesne - One of the best experts on this subject based on the ideXlab platform.
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on the power transformation of kernel based tests for serial correlation in vector time series some finite sample results and a comparison with the bootstrap
Computational Statistics & Data Analysis, 2008Co-Authors: Jennifer Poulin, Pierre DuchesneAbstract:Portmanteau test statistics represent useful diagnostic tools for checking the adequacy of multivariate time series models. For stationary and partially non-stationary vector time series models, Duchesne and Roy [Duchesne, P., Roy, R., 2004. On consistent testing for serial correlation of unknown form in vector time series models. Journal of Multivariate Analysis 89, 148-180] and Duchesne [Duchesne, P., 2005a. Testing for serial correlation of unknown form in cointegrated time series models. Annals of the Institute of Statistical Mathematics 57, 575-595] have proposed kernel-based test statistics, obtained by comparing the spectral density of the errors under the null hypothesis of non-correlation with a kernel-based spectral density estimator; these test statistics are asymptotically standard normal under the null hypothesis of non-correlation in the error term of the model. Following the method of Chen and Deo [Chen, W.W., Deo, R.S., 2004a. Power transformations to induce normality and their applications. Journal of the Royal Statistical Society, Ser. B 66, 117-130], we determine an appropriate power transformation to improve the normal approximation in small samples. Additional corrections for the mean and variance of the distance measures intervening in these test statistics are obtained. An alternative procedure to estimate the finite distribution of the test statistics is to use the bootstrap method; we introduce bootstrap-based versions of the original spectral test statistics. In a Monte Carlo study, comparisons are made under various alternatives between: the original spectral test statistics, the new corrected test statistics, the bootstrap-based versions, and finally the classical Hosking portmanteau test statistic.
Jennifer Poulin - One of the best experts on this subject based on the ideXlab platform.
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on the power transformation of kernel based tests for serial correlation in vector time series some finite sample results and a comparison with the bootstrap
Computational Statistics & Data Analysis, 2008Co-Authors: Jennifer Poulin, Pierre DuchesneAbstract:Portmanteau test statistics represent useful diagnostic tools for checking the adequacy of multivariate time series models. For stationary and partially non-stationary vector time series models, Duchesne and Roy [Duchesne, P., Roy, R., 2004. On consistent testing for serial correlation of unknown form in vector time series models. Journal of Multivariate Analysis 89, 148-180] and Duchesne [Duchesne, P., 2005a. Testing for serial correlation of unknown form in cointegrated time series models. Annals of the Institute of Statistical Mathematics 57, 575-595] have proposed kernel-based test statistics, obtained by comparing the spectral density of the errors under the null hypothesis of non-correlation with a kernel-based spectral density estimator; these test statistics are asymptotically standard normal under the null hypothesis of non-correlation in the error term of the model. Following the method of Chen and Deo [Chen, W.W., Deo, R.S., 2004a. Power transformations to induce normality and their applications. Journal of the Royal Statistical Society, Ser. B 66, 117-130], we determine an appropriate power transformation to improve the normal approximation in small samples. Additional corrections for the mean and variance of the distance measures intervening in these test statistics are obtained. An alternative procedure to estimate the finite distribution of the test statistics is to use the bootstrap method; we introduce bootstrap-based versions of the original spectral test statistics. In a Monte Carlo study, comparisons are made under various alternatives between: the original spectral test statistics, the new corrected test statistics, the bootstrap-based versions, and finally the classical Hosking portmanteau test statistic.
Rauf M Ahmad - One of the best experts on this subject based on the ideXlab platform.
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a u statistic approach for a high dimensional two sample mean testing problem under non normality and behrens fisher setting
Annals of the Institute of Statistical Mathematics, 2014Co-Authors: Rauf M AhmadAbstract:A two-sample test statistic is presented for testing the equality of mean vectors when the dimension, $$p$$ , exceeds the sample sizes, $$n_i,\; i=1, 2$$ , and the distributions are not necessarily normal. Under mild assumptions on the traces of the covariance matrices, the statistic is shown to be asymptotically Chi-square distributed when $$n_i, p \rightarrow \infty $$ . However, the validity of the test statistic when $$p$$ is fixed but large, including $$p > n_i$$ , and when the distributions are multivariate normal, is shown as special cases. This two-sample Chi-square approximation helps us establish the validity of Box’s approximation for high-dimensional and non-normal data to a two-sample setup, valid even under Behrens–Fisher setting. The limiting Chi-square distribution of the statistic is obtained using the asymptotic theory of degenerate $$U$$ -statistics, and using a result from classical asymptotic theory, it is further extended to an approximate normal distribution. Both independent and paired-sample cases are considered. Copyright The Institute of Statistical Mathematics, Tokyo 2014
De Las Casas Tomas Irma - One of the best experts on this subject based on the ideXlab platform.
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Métodos automatizados en el aprendizaje de cálculo de engranajes en la formación del Ingeniero Mecánico/ Automated methods in the learning of calculation of gears in the formation of the mechanical engineer
Universidad de Camagüey Ignacio Agramonte Loynaz, 2020Co-Authors: Martínez Delfín Angel, De Las Casas Tomas IrmaAbstract:Objective: The paper aims at devising an alternative for teaching and learning how to calculate the capacity of the load of the cylindrical gears with the use of automated methods. This alternative is based on a mathematic model of the locus of the points of the contour of the teeth in polar coordinates. Methods: Using synthetic analytical methods and Statistical Mathematics, it was possible to perform the referred calculation and proposing a teaching method. Results: The text illustrated that it is possible to instruct the students to calculate gear load capacity by means of automated procedures. Likewise, the need for a new teaching method to deal with gears is argued. This method fosters students learning of professional techniques to examine gears and how to distinguish worn-out properties. Conclusion: The introduction of automated methods to learn how to calculate the capacity of the load of the cylindrical gears facilitates students learning and the development of professional competencies of the would-be mechanical engineer. Objetivo: El artículo tiene como objetivo ofrecer una alternativa que facilite el procesamiento del cálculo de la capacidad de carga de los engranajes cilíndricos con empleo de métodos automatizados en la asignatura Elementos de Máquinas, esta opción está basada en un modelo matemático del lugar geométrico de los puntos del contorno de los dientes en coordenadas polares. Métodos: Los métodos analíticos sintéticos y el matemático estadístico posibilitaron el diseño de la propuesta y la realización del cálculo de capacidad ya referido. Resultados: Se demuestra cómo es posible que los estudiantes aprendan a realizar estos cálculos con el auxilio de métodos automatizados desde la asignatura Elementos de Máquina en la carrera del Ingeniero Mecánico. De igual forma, se definió la necesidad de un nuevo método para los temas relacionados con los engranajes, garantizando así el aprendizaje de la forma de trabajo de los principales deterioros de los mismos y en función de ello, las comprobaciones necesarias a realizar. Conclusión: La introducción de métodos de cálculo automatizados en el aprendizaje de cálculo de la capacidad de carga de los engranajes facilita el aprendizaje de los estudiantes y el desarrollo de competencias profesionales del futuro ingeniero mecánico
Liu F - One of the best experts on this subject based on the ideXlab platform.
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High-dimensional sign-constrained feature selection and grouping
'Springer Science and Business Media LLC', 2021Co-Authors: Qin S, Ding H, Wu Y, Liu FAbstract:© 2020, The Institute of Statistical Mathematics, Tokyo. In this paper, we propose a non-negative feature selection/feature grouping (nnFSG) method for general sign-constrained high-dimensional regression problems that allows regression coefficients to be disjointly homogeneous, with sparsity as a special case. To solve the resulting non-convex optimization problem, we provide an algorithm that incorporates the difference of convex programming, augmented Lagrange and coordinate descent methods. Furthermore, we show that the aforementioned nnFSG method recovers the oracle estimate consistently, and that the mean-squared errors are bounded. Additionally, we examine the performance of our method using finite sample simulations and applying it to a real protein mass spectrum dataset
