Algorithms sequential and parallel: a unified approach - download pdf or read online

By Miller R., Boxer L.

ISBN-10: 0130863734

ISBN-13: 9780130863737

For a one-semester, junior/senior-level path in Algorithms. Attuned to the quickly altering panorama in machine know-how, this particular and extremely revolutionary textual content is helping scholars comprehend the applying and research of algorithmic paradigms to either the conventional sequential version of computing and to quite a few parallel models-offering a unified, totally built-in insurance of either version kinds in order that scholars can learn how to realize how resolution concepts might be shared between desktop paradigms and architectures

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24–27. Meng, X. , Rubin, D. B. (1991). Using EM to obtain asymptotic variance– covariance matrices—the SEM algorithm. J. Am. Stat. Assoc. 86:899–909. Meng, X. , Rubin, D. B. (1993). Maximum likelihood estimation via the ECM algorithm: a general framework. Biometrika 80:267–278. , Woodbury, M. A. (1972). A missing information principle: theory and applications. Proceedings of the 6th Berkeley Symposium on Mathematical Statistics and Probability Vol. 1:697–715. Rubin, D. B. (1987a). Multiple Imputation for Nonresponse in Surveys.

B. (1991). Using EM to obtain asymptotic variance– covariance matrices—the SEM algorithm. J. Am. Stat. Assoc. 86:899–909. Meng, X. , Rubin, D. B. (1993). Maximum likelihood estimation via the ECM algorithm: a general framework. Biometrika 80:267–278. , Woodbury, M. A. (1972). A missing information principle: theory and applications. Proceedings of the 6th Berkeley Symposium on Mathematical Statistics and Probability Vol. 1:697–715. Rubin, D. B. (1987a). Multiple Imputation for Nonresponse in Surveys.

2). If the number of variables is small, the exclusion method can perform a sufficiently efficient estimation. However, if there are many variables, its estimation efficiency is inferior to the other two processing methods of estimating the missing values. Put differently, the relative efficiency of the methods of estimating the missing values varies with the extent to which the variables are correlated with each other. This means that the efficiency of mean value imputation is the highest when 14 Watanabe and Yamaguchi Figure 2 Relative efficiency of estimates of covariance matrix.

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Algorithms sequential and parallel: a unified approach by Miller R., Boxer L.


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