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	Computational Statistics & Data Analysis Elsevier Science Publishers B. V.         Options: Date Reviewed Title Author Publisher Published Date Descending Order Ascending Order     1-10 of 10 reviews Date Reviewed      A fast approximate EM algorithm for joint models of survival and multivariate longitudinal data Murray J., Philipson P. Computational Statistics & Data Analysis 170(1): 1-15, 2022.  Type: Article Many longitudinal clinical studies involve the repeated periodic measurement of continuous responses over a period to detect any changes that might occur in the condition of the individual, such as events of interest like survival after 90 days. I... May 4 2023   Parallel-and-stream accelerator for computationally fast supervised learning Hector E., Luo L., Song P. Computational Statistics & Data Analysis 177(1): 1-12, 2022.  Type: Article Large enterprises with massive amounts of data require reliable and efficient algorithms for exploring and forecasting trends in available supplies, user purchases, and advertisements. The scalability of the MapReduce approach is advantageous for ... Feb 20 2023   A new nonparametric screening method for ultrahigh-dimensional survival data Liu Y., Zhang J., Zhao X. Computational Statistics & Data Analysis 119(C): 74-85, 2018.  Type: Article Groundbreaking effective algorithms for overcoming the discrepancies in the existing screening procedures for ultrahigh-dimensional medical survival data are long overdue. Liu et al. offer a nonparametric Kolmogorov-Smirnov (K-S) test ... May 31 2018   Software article: analysis of the Oracle-based epilepsy database with SAS; enterprise guide software Zoumba N., Lochmann T., Ortseifen C., Bast T., Ramantani G., Rating D. Computational Statistics & Data Analysis 43(3): 399-404, 2003.  Type: Article During pre-surgical epilepsy diagnosis at the University of Heidelberg’s Department of Pediatrics, a large amount of data relevant to diagnostic decisions and scientific research is stored in an Oracle-based epilepsy database... Apr 2 2004   Improved estimation of clutter properties in speckled imagery: how to write them and why Cribari-Neto F., Frery A., Silva M. Computational Statistics & Data Analysis 40(4): 801-824, 2002.  Type: Article When it comes to cooking, salt and pepper are essential to the chef; but when it comes to imagery, researchers would be better off without it. Speckle noise, otherwise known as the salt and pepper effect, corrupts the ground truth when... Jul 2 2003   Comparison of group screening strategies for factorial experiments: how to write them and why Dean A., Lewis S. Computational Statistics & Data Analysis 39(3): 287-297, 2002.  Type: Article An important aim of experimentation is to identify design factors and settings that achieve a required mean performance, while minimizing performance variability due to varying noise factors. An initial screening experiment must then b... Jun 18 2003   A graphical method for evaluating slope-rotatability in axial directions for second order response surface designs Jang D. Computational Statistics & Data Analysis 39(3): 343-349, 2002.  Type: Article One of the more important pieces of knowledge that we have about nature is the law of least squares. This is the equivalent of finding a vector projection, in a known vector space, of some observational vector that satisfies the least ... Jun 12 2003   Weighted tests of homogeneity for testing the number of components in a mixture Susko E. Computational Statistics & Data Analysis 41(3-4): 367-378, 2003.  Type: Article When conducting a test that requires a large, or even moderately sized, sample, there are many instances when the sample consists of more than one subpopulation. This can obscure the true result for each of the subpopulations. There ar... May 28 2003    Influence diagnostics for generalized linear mixed models: applications to clustered data Xiang L., Tse S., Lee A. Computational Statistics & Data Analysis 40(4): 759-774, 2002.  Type: Article The generalized linear mixed model (GLMM) is one of many extensions of the usual linear model. In a GLMM, observations are not necessarily independent, but it is assumed that data can be clustered so that observations in different clus... Apr 17 2003   Implementation of higher-order asymptotics to S-plus Yi G., Wu J., Liu Y. Computational Statistics & Data Analysis 40(4): 775-800, 2002.  Type: Article The usual approach for Cox regression is to use twice the log likelihood-ratio statistic, which is referred to in this paper as R2, and the chi-square. This paper is concerned with higher-order expansions that involve the second and th... Apr 8 2003       Display 510152550100 per column
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