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21.
张勤 《汕头大学学报(人文社会科学版)》2011,27(1):81-87,96,3
香港的律师制度渊源于英国,在律师团体管理方面表现出自主性、自律性的特点,具有典型的法律职业主义色彩。香港的律师惩戒制度作为体现上述特点的主要内容之一,具有民主性、程序性、公正性和司法性特征。具有法律职业主义色彩的律师伦理规范和律师惩戒制度,体现了社会一部分职业相对于国家所具有的独立性,但同时也是律师团体通过自我控制实现市场垄断所作出的努力。香港律师团体管理模式中所具有的这种两面性为大陆律师管理模式的改革和完善提供了很难得的研究样本。 相似文献
22.
《Journal of Statistical Computation and Simulation》2012,82(3):538-551
Generally, confidence regions for the probabilities of a multinomial population are constructed based on the Pearson χ2 statistic. Morales et al. (Bootstrap confidence regions in multinomial sampling. Appl Math Comput. 2004;155:295–315) considered the bootstrap and asymptotic confidence regions based on a broader family of test statistics known as power-divergence test statistics. In this study, we extend their work and propose penalized power-divergence test statistics-based confidence regions. We only consider small sample sizes where asymptotic properties fail and alternative methods are needed. Both bootstrap and asymptotic confidence regions are constructed. We consider the percentile and the bias corrected and accelerated bootstrap confidence regions. The latter confidence region has not been studied previously for the power-divergence statistics much less for the penalized ones. Designed simulation studies are carried out to calculate average coverage probabilities. Mean absolute deviation between actual and nominal coverage probabilities is used to compare the proposed confidence regions. 相似文献
23.
《Stat》2018,7(1)
A method is introduced for variable selection and prediction in linear regression problems where the number of predictors can be much larger than the number of observations. The methodology involves minimizing a penalized Euclidean distance, where the penalty is the geometric mean of the ℓ1 and ℓ2 norms of regression coefficients. This particular formulation exhibits a grouping effect, which is useful for model selection in high‐dimensional problems. Also, an important result is a model consistency theorem, which does not require an estimate of the noise standard deviation. An algorithm for estimation is described, which involves thresholding to obtain a sparse solution. Practical performances of variable selection and prediction are evaluated through simulation studies and the analysis of real datasets. © 2018 The Authors. Stat Published by John Wiley & Sons Ltd. 相似文献
24.
Clifford Lam 《Econometric Reviews》2016,35(8-10):1347-1376
In many economic applications, it is often of interest to categorize, classify, or label individuals by groups based on similarity of observed behavior. We propose a method that captures group affiliation or, equivalently, estimates the block structure of a neighboring matrix embedded in a Spatial Econometric model. The main results of the Least Absolute Shrinkage and Selection Operator (Lasso) estimator shows that off-diagonal block elements are estimated as zeros with high probability, property defined as “zero-block consistency.” Furthermore, we present and prove zero-block consistency for the estimated spatial weight matrix even under a thin margin of interaction between groups. The tool developed in this article can be used as a verification of block structure by applied researchers, or as an exploration tool for estimating unknown block structures. We analyzed the U.S. Senate voting data and correctly identified blocks based on party affiliations. Simulations also show that the method performs well. 相似文献
25.
In this article, we develop a generalized penalized linear unbiased selection (GPLUS) algorithm. The GPLUS is designed to compute the paths of penalized logistic regression based on the smoothly clipped absolute deviation (SCAD) and the minimax concave penalties (MCP). The main idea of the GPLUS is to compute possibly multiple local minimizers at individual penalty levels by continuously tracing the minimizers at different penalty levels. We demonstrate the feasibility of the proposed algorithm in logistic and linear regression. The simulation results favor the SCAD and MCP’s selection accuracy encompassing a suitable range of penalty levels. 相似文献
26.
《Journal of Statistical Computation and Simulation》2012,82(9):1904-1916
Two-different types of adjustments to the power-divergence test statistics have been introduced for the problem of testing goodness-of-fit under clustered sampling. Penalization has also been introduced to handle the cells with zero frequencies. The asymptotic distribution of the proposed power-divergence test statistics has been investigated under clustered sampling and the performances of the proposed statistics for finite samples have been studied through a designed simulation study. 相似文献
27.
Hiba Alawieh Nicolas Wicker Baydaa Al Ayoubi Luc Moulinier 《Journal of applied statistics》2017,44(15):2697-2715
The three-dimensional structure of a given protein can take different conformations depending upon the reaction it undergoes and its substrate/cofactor/partners binding state. Various methods exist to study these conformational changes but only one, called DynDom, is clearly focused on movement detection. An alternative method is proposed, making use of multivariate data analysis, called ‘penalized Multidimensional Fitting (penalized MDF)’ based on penalized movements of points in order to approach the distances between points after movement to the distances given by the reference matrix. The objective is to detect the amino acids that undergo an important movement by fitting the distances of one conformation to the distances of the second one by modifying only the coordinates of the first one. This method is applied to three different proteins. 相似文献
28.
Jia Yuan Hu;Marley DeSimone;Qing Wang; 《Stat》2024,13(2):e675
Mediation analysis intends to unveil the underlying relationship between an outcome variable and an exposure variable through one or more intermediate variables called mediators. In recent decades, research on mediation analysis has been focusing on multivariate mediation models, where the number of mediating variables is possibly of high dimension. This paper concerns high-dimensional mediation analysis and proposes a three-step algorithm that extracts and utilizes inter-connectivity among candidate mediators. More specifically, the proposed methodology starts with a screening procedure to reduce the dimensionality of the initial set of candidate mediators, followed by a penalized regression model that incorporates both parameter- and group-wise regularization, and ends with fitting a multivariate mediation model and identifying active mediating variables through a joint significance test. To showcase the performance of the proposed algorithm, we conducted two simulation studies in high-dimensional and ultra-high-dimensional settings, respectively. Furthermore, we demonstrate the practical applications of the proposal using a real data set that uncovers the possible impact of environmental toxicants on women's gestational age at delivery through 61 biomarkers that belong to 7 biological pathways. 相似文献