• Title/Summary/Keyword: procrustes problem

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THE PERIODIC JACOBI MATRIX PROCRUSTES PROBLEM

  • Li, Jiao-Fen;Hu, Xi-Yan
    • Journal of applied mathematics & informatics
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    • v.28 no.3_4
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    • pp.569-582
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    • 2010
  • The following "Periodic Jacobi Procrustes" problem is studied: find the Periodic Jacobi matrix X which minimizes the Frobenius (or Euclidean) norm of AX - B, with A and B as given rectangular matrices. The class of Procrustes problems has many application in the biological, physical and social sciences just as in the investigation of elastic structures. The different problems are obtained varying the structure of the matrices belonging to the feasible set. Higham has solved the orthogonal, the symmetric and the positive definite cases. Andersson and Elfving have studied the symmetric positive semidefinite case and the (symmetric) elementwise nonnegative case. In this contribution, we extend and develop these research, however, in a relatively simple way. Numerical difficulties are discussed and illustrated by examples.

A Study on Shape Variability in Canonical Correlation Biplot with Missing Values (결측값이 있는 정준상관 행렬도의 형상변동 연구)

  • Hong, Hyun-Uk;Choi, Yong-Seok;Shin, Sang-Min;Ka, Chang-Wan
    • The Korean Journal of Applied Statistics
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    • v.23 no.5
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    • pp.955-966
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    • 2010
  • Canonical correlation biplot is a useful biplot for giving a graphical description of the data matrix which consists of the association between two sets of variables, for detecting patterns and displaying results found by more formal methods of analysis. Nevertheless, when some values are missing in data, most biplots are not directly applicable. To solve this problem, we estimate the missing data using the median, mean, EM algorithm and MCMC imputation methods according to missing rates. Even though we estimate the missing values of biplot of incomplete data, we have different shapes of biplots according to the imputation methods and missing rates. Therefore we use a RMS(root mean square) which was proposed by Shin et al. (2007) and PS(procrustes statistic) for measuring and comparing the shape variability between the original biplots and the estimated biplots.