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题目说的不清楚。先把help文档贴上来: 
 corr Linear or rank correlation. 
    RHO = corr(X) returns a P-by-P matrix containing the pairwise linear 
    correlation coefficient between each pair of columns in the N-by-P 
    matrix X. 
 
    RHO = corr(X,Y,...) returns a P1-by-P2 matrix containing the pairwise 
    correlation coefficient between each pair of columns in the N-by-P1 and 
    N-by-P2 matrices X and Y. 
 
    [RHO,PVAL] = corr(...) also returns PVAL, a matrix of p-values for 
    testing the hypothesis of no correlation against the alternative that 
    there is a non-zero correlation.  Each element of PVAL is the p-value 
    for the corresponding element of RHO.  If PVAL(i,j) is small, say less 
    than 0.05, then the correlation RHO(i,j) is significantly different 
    from zero. 
 
    [...] = corr(...,'PARAM1',VAL1,'PARAM2',VAL2,...) specifies additional 
    parameters and their values.  Valid parameters are the following: 
 
         Parameter  Value 
          'type'    'Pearson' (the default) to compute Pearson's linear 
                    correlation coefficient, 'Kendall' to compute Kendall's 
                    tau, or 'Spearman' to compute Spearman's rho. 
          'rows'    'all' (default) to use all rows regardless of missing 
                    values (NaNs), 'complete' to use only rows with no 
                    missing values, or 'pairwise' to compute RHO(i,j) using 
                    rows with no missing values in column i or j. 
          'tail'    The alternative hypothesis against which to compute 
                    p-values for testing the hypothesis of no correlation. 
                    Choices are: 
                       TAIL         Alternative Hypothesis 
                    --------------------------------------------------- 
                      'both'     correlation is not zero (the default) 
                      'right'    correlation is greater than zero 
                      'left'     correlation is less than zero 
 
    The 'pairwise' option for the 'rows' parameter can produce RHO that is not 
    positive definite.  The 'complete' option always produces a positive 
    definite RHO, but when data are missing, the estimates may be based on 
    fewer observations. 
 
看这个文档中‘rows’选项的介绍,分不清pairwise和complete的区别。最后好像提到他们的区别是最终那个相关系数矩阵是不是正定的。我不懂这个到底代表着什么含义,“正定”或者“不正定”有什么差别,pairwise和complete两个选项具体执行过程是怎样的,有什么差别。 
谢谢大家了! 
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