急求！！corrcoef（X'）出现的矩阵中有一行一列都是NaN怎么办
我将一组数据归一化后得到：X=[
0.30406 0.42166 0.10803 0.04228 0.19040
0.14375 0.23663 0.20215 0.07292 0.12177
0.43544 0.35541 0.18663 0.03484 0.52739
0.16878 0.14623 0.16664 0.00526 0.33336
0.13996 0.31231 0.22833 0.02988 0.20139
0.33730 0.49316 0.29782 0.12475 0.42676
0.14435 0.21900 0.07913 0.02367 0.13561
0.23287 0.70773 0.43657 0.02969 0.20401
0.41344 0.47421 0.32271 0.42811 0.32469
0.79015 0.80677 0.48430 0.21283 0.75542
0.60780 0.60806 0.61804 0.18940 0.58265
0.23335 0.14251 0.16559 0.01418 0.19292
0.28792 0.40717 0.30047 0.05186 0.25693
0.16255 0.10452 0.17560 0.02917 0.13825
0.79114 0.50356 0.55850 0.18081 0.70091
0.43958 0.47637 0.25096 0.04900 0.53094
0.28085 0.66818 0.35671 0.05549 0.27205
0.28132 0.33360 0.21903 0.02260 0.25618
1.00000 1.00000 1.00000 1.00000 1.00000
0.16128 0.26053 0.26279 0.01791 0.16744
0.01809 0.04041 0.03006 0.00240 0.00000
0.12103 0.13831 0.14567 0.00138 0.10369
0.32141 0.43474 0.24584 0.00386 0.34003
0.06586 0.11708 0.08449 0.00531 0.22196
0.14218 0.21982 0.21481 0.00349 0.17534
0.14727 0.29759 0.17386 0.02458 0.16870
0.06644 0.14086 0.08199 0.00867 0.16534
0.00000 0.00000 0.00000 0.00000 0.05649
0.00386 0.04338 0.04502 0.00116 0.08806
0.09474 0.21852 0.17225 0.01169 0.08507
];
而用corrcoef(X')得到的结果是：
ans =
Columns 1 through 12
1.0000 0.6540 0.6320 0.2785 0.6869 0.8296 0.9680 0.7155 0.5349 0.8620 0.6286 0.5272
0.6540 1.0000 0.2310 0.1991 0.9187 0.6943 0.6956 0.9769 0.1427 0.5360 0.7431 0.4135
0.6320 0.2310 1.0000 0.8695 0.4927 0.8095 0.7324 0.2293 -0.1817 0.9229 0.7321 0.8376
0.2785 0.1991 0.8695 1.0000 0.5102 0.7030 0.4730 0.1609 -0.6001 0.7055 0.7183 0.7609
0.6869 0.9187 0.4927 0.5102 1.0000 0.8871 0.8054 0.9282 -0.0070 0.6946 0.8145 0.5072
0.8296 0.6943 0.8095 0.7030 0.8871 1.0000 0.9423 0.7348 0.0495 0.9180 0.8202 0.6629
0.9680 0.6956 0.7324 0.4730 0.8054 0.9423 1.0000 0.7562 0.3547 0.9179 0.7261 0.5909
0.7155 0.9769 0.2293 0.1609 0.9282 0.7348 0.7562 1.0000 0.2777 0.5397 0.6562 0.3032
0.5349 0.1427 -0.1817 -0.6001 -0.0070 0.0495 0.3547 0.2777 1.0000 0.0671 -0.2783 -0.3473
0.8620 0.5360 0.9229 0.7055 0.6946 0.9180 0.9179 0.5397 0.0671 1.0000 0.8409 0.8388
0.6286 0.7431 0.7321 0.7183 0.8145 0.8202 0.7261 0.6562 -0.2783 0.8409 1.0000 0.9039
0.5272 0.4135 0.8376 0.7609 0.5072 0.6629 0.5909 0.3032 -0.3473 0.8388 0.9039 1.0000
0.8181 0.9136 0.6028 0.4986 0.9409 0.8949 0.8808 0.8917 0.0744 0.8301 0.9114 0.6962
0.2780 0.5082 0.5787 0.6652 0.5244 0.4967 0.3641 0.3458 -0.5580 0.6024 0.8955 0.9087
0.4984 0.3156 0.8728 0.7899 0.4386 0.6408 0.5645 0.2127 -0.3629 0.8356 0.8579 0.9932
0.7649 0.4534 0.9667 0.8270 0.6872 0.9312 0.8681 0.4670 -0.0731 0.9751 0.8149 0.8152
0.8275 0.9371 0.3933 0.2675 0.9430 0.8417 0.8719 0.9790 0.3194 0.6784 0.6996 0.3889
0.8582 0.7599 0.7980 0.6433 0.8534 0.9388 0.9231 0.7406 0.0361 0.9527 0.9334 0.8239
NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
0.5655 0.9413 0.4169 0.4792 0.9389 0.7577 0.6662 0.8784 -0.1687 0.6270 0.8935 0.6210
0.6120 0.9448 -0.0057 -0.1156 0.7486 0.4820 0.5759 0.9235 0.3557 0.3610 0.5548 0.2376
0.6138 0.8558 0.5773 0.5801 0.8628 0.7737 0.6969 0.7657 -0.2160 0.7500 0.9763 0.8096
0.8625 0.7390 0.8190 0.6772 0.8745 0.9770 0.9462 0.7439 0.0459 0.9562 0.9001 0.7739
0.3188 0.2299 0.8076 0.9454 0.5854 0.7637 0.5333 0.2550 -0.4627 0.6615 0.6048 0.5611
0.5858 0.8727 0.5735 0.6425 0.9452 0.8401 0.7155 0.8166 -0.2506 0.7249 0.9408 0.7100
0.8303 0.9068 0.5495 0.4536 0.9748 0.9251 0.9090 0.9369 0.1772 0.7803 0.7988 0.5246
0.5682 0.5083 0.7968 0.8507 0.8043 0.9237 0.7551 0.5531 -0.2278 0.7803 0.7184 0.5726
-0.0841 -0.2901 0.6213 0.8129 0.1009 0.3611 0.1161 -0.2546 -0.5685 0.3155 0.1848 0.2911
0.1123 0.2717 0.5712 0.8477 0.6011 0.6410 0.3574 0.2913 -0.5738 0.4331 0.5083 0.3693
0.6541 0.9967 0.2676 0.2544 0.9461 0.7322 0.7138 0.9811 0.1110 0.5561 0.7547 0.4181
Columns 13 through 24
0.8181 0.2780 0.4984 0.7649 0.8275 0.8582 NaN 0.5655 0.6120 0.6138 0.8625 0.3188
0.9136 0.5082 0.3156 0.4534 0.9371 0.7599 NaN 0.9413 0.9448 0.8558 0.7390 0.2299
0.6028 0.5787 0.8728 0.9667 0.3933 0.7980 NaN 0.4169 -0.0057 0.5773 0.8190 0.8076
0.4986 0.6652 0.7899 0.8270 0.2675 0.6433 NaN 0.4792 -0.1156 0.5801 0.6772 0.9454
0.9409 0.5244 0.4386 0.6872 0.9430 0.8534 NaN 0.9389 0.7486 0.8628 0.8745 0.5854
0.8949 0.4967 0.6408 0.9312 0.8417 0.9388 NaN 0.7577 0.4820 0.7737 0.9770 0.7637
0.8808 0.3641 0.5645 0.8681 0.8719 0.9231 NaN 0.6662 0.5759 0.6969 0.9462 0.5333
0.8917 0.3458 0.2127 0.4670 0.9790 0.7406 NaN 0.8784 0.9235 0.7657 0.7439 0.2550
0.0744 -0.5580 -0.3629 -0.0731 0.3194 0.0361 NaN -0.1687 0.3557 -0.2160 0.0459 -0.4627
0.8301 0.6024 0.8356 0.9751 0.6784 0.9527 NaN 0.6270 0.3610 0.7500 0.9562 0.6615
0.9114 0.8955 0.8579 0.8149 0.6996 0.9334 NaN 0.8935 0.5548 0.9763 0.9001 0.6048
0.6962 0.9087 0.9932 0.8152 0.3889 0.8239 NaN 0.6210 0.2376 0.8096 0.7739 0.5611
1.0000 0.6581 0.6302 0.7694 0.9289 0.9584 NaN 0.9344 0.7835 0.9400 0.9446 0.4887
0.6581 1.0000 0.8712 0.5818 0.3485 0.6933 NaN 0.7315 0.3465 0.8641 0.6230 0.4415
0.6302 0.8712 1.0000 0.8257 0.3144 0.7864 NaN 0.5374 0.1304 0.7415 0.7430 0.5904
0.7694 0.5818 0.8257 1.0000 0.6141 0.9085 NaN 0.5907 0.2232 0.7013 0.9340 0.8083
0.9289 0.3485 0.3144 0.6141 1.0000 0.8283 NaN 0.8528 0.8567 0.7718 0.8424 0.3667
0.9584 0.6933 0.7864 0.9085 0.8283 1.0000 NaN 0.8293 0.5971 0.9010 0.9906 0.6028
NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
0.9344 0.7315 0.5374 0.5907 0.8528 0.8293 NaN 1.0000 0.7984 0.9602 0.8071 0.4545
0.7835 0.3465 0.1304 0.2232 0.8567 0.5971 NaN 0.7984 1.0000 0.7059 0.5546 -0.0942
0.9400 0.8641 0.7415 0.7013 0.7718 0.9010 NaN 0.9602 0.7059 1.0000 0.8599 0.4824
0.9446 0.6230 0.7430 0.9340 0.8424 0.9906 NaN 0.8071 0.5546 0.8599 1.0000 0.6758
0.4887 0.4415 0.5904 0.8083 0.3667 0.6028 NaN 0.4545 -0.0942 0.4824 0.6758 1.0000
0.9391 0.7708 0.6445 0.7192 0.8239 0.8826 NaN 0.9795 0.6775 0.9663 0.8738 0.6170
0.9646 0.4636 0.4620 0.7437 0.9799 0.9039 NaN 0.8863 0.7691 0.8359 0.9228 0.5310
0.7183 0.4466 0.5722 0.8770 0.6564 0.7783 NaN 0.6515 0.2194 0.6427 0.8467 0.9412
-0.0170 0.1551 0.3674 0.5121 -0.1378 0.1576 NaN -0.0367 -0.5836 0.0160 0.2432 0.8608
0.4126 0.3749 0.3802 0.6033 0.3438 0.4474 NaN 0.4869 -0.0494 0.4360 0.5276 0.9413
0.9221 0.5058 0.3238 0.4898 0.9480 0.7741 NaN 0.9509 0.9183 0.8595 0.7628 0.2996
Columns 25 through 30
0.5858 0.8303 0.5682 -0.0841 0.1123 0.6541
0.8727 0.9068 0.5083 -0.2901 0.2717 0.9967
0.5735 0.5495 0.7968 0.6213 0.5712 0.2676
0.6425 0.4536 0.8507 0.8129 0.8477 0.2544
0.9452 0.9748 0.8043 0.1009 0.6011 0.9461
0.8401 0.9251 0.9237 0.3611 0.6410 0.7322
0.7155 0.9090 0.7551 0.1161 0.3574 0.7138
0.8166 0.9369 0.5531 -0.2546 0.2913 0.9811
-0.2506 0.1772 -0.2278 -0.5685 -0.5738 0.1110
0.7249 0.7803 0.7803 0.3155 0.4331 0.5561
0.9408 0.7988 0.7184 0.1848 0.5083 0.7547
0.7100 0.5246 0.5726 0.2911 0.3693 0.4181
0.9391 0.9646 0.7183 -0.0170 0.4126 0.9221
0.7708 0.4636 0.4466 0.1551 0.3749 0.5058
0.6445 0.4620 0.5722 0.3674 0.3802 0.3238
0.7192 0.7437 0.8770 0.5121 0.6033 0.4898
0.8239 0.9799 0.6564 -0.1378 0.3438 0.9480
0.8826 0.9039 0.7783 0.1576 0.4474 0.7741
NaN NaN NaN NaN NaN NaN
0.9795 0.8863 0.6515 -0.0367 0.4869 0.9509
0.6775 0.7691 0.2194 -0.5836 -0.0494 0.9183
0.9663 0.8359 0.6427 0.0160 0.4360 0.8595
0.8738 0.9228 0.8467 0.2432 0.5276 0.7628
0.6170 0.5310 0.9412 0.8608 0.9413 0.2996
1.0000 0.8935 0.7747 0.1532 0.6163 0.8942
0.8935 1.0000 0.7800 0.0363 0.4849 0.9275
0.7747 0.7800 1.0000 0.6535 0.8804 0.5696
0.1532 0.0363 0.6535 1.0000 0.8110 -0.2177
0.6163 0.4849 0.8804 0.8110 1.0000 0.3453
0.8942 0.9275 0.5696 -0.2177 0.3453 1.0000
这是什么原因呢？如果是因为原矩阵中有0的关系；我另一组数据中也有0，但求出的数据却没有NaN。
请能人帮忙分析一下，不甚感激！！！
没人回答吗？ 没人回答吗？ 回复 ssxy60 的帖子
有两行相乘等于0的情况（倒数第3行和倒数第10行），这样会导致分母为0 当然会出现NA了 回复 水木年华zzu 的帖子
那要怎么解决呢? 回复 ssxy60 的帖子
是数据的问题，分析下数据为什么会是这样子
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