[問題]1與0的判別
我在matlab讀取txt檔的一組隨機變數
打算算出correlation及partial correlation
並print出1與0的矩陣(若係數>0.5 輸出1)
結果發現
-0.0000 輸出0 (正確無誤)
+0.0000 輸出1
這.......?? 0.0000不是小於0.5嗎?
怎麼會出現1(出現在最後面的inv函數print)
是我給的指令模糊還是???
以下是matlab的指令：
>> x=textread('random_data.txt')
x =
0.2281 0.7281 0.0319 0.9559 0.9878 -0.7681 0.8738 0.6260
0.1514 0.6514 0.6151 0.8942 1.5093 -0.1849 0.7641 1.0481
0.5635 1.0635 0.7624 0.5885 1.3508 -0.0376 0.4866 1.0643
0.1923 0.6923 0.0008 0.9607 0.9615 -0.7992 0.5712 0.3472
0.0032 0.5032 0.1191 0.4217 0.5407 -0.6809 0.9573 0.5122
0.6682 1.1682 0.3829 0.7281 1.1110 -0.4171 0.1123 0.9830
0.2065 0.7065 0.3480 0.7218 1.0698 -0.4520 0.1988 0.7952
0.0626 0.5626 0.6504 0.9633 1.6137 -0.1496 0.9971 1.4059
0.1085 0.6085 0.2936 0.2348 0.5284 -0.5064 0.9929 1.0454
0.9119 1.4119 0.2665 0.7653 1.0318 -0.5335 0.1699 0.6831
0.6496 1.1496 0.8974 0.4412 1.3387 0.0974 0.3149 1.4623
0.5028 1.0028 0.5651 0.2375 0.8026 -0.2349 0.2446 1.1811
0.2853 0.7853 0.0142 0.3294 0.3436 -0.7858 0.8018 0.9021
0.3002 0.8002 0.2119 0.5849 0.7968 -0.5881 0.6369 0.6458
0.5836 1.0836 0.0000 0.7009 0.7009 -0.8000 0.4170 0.3947
0.5805 1.0805 0.1375 0.6684 0.8059 -0.6625 0.0527 0.5681
0.6142 1.1142 0.2614 0.5642 0.8256 -0.5386 0.1015 0.5231
0.0823 0.5823 0.3378 0.8615 1.1993 -0.4622 0.3439 0.8322
0.0455 0.5455 0.5043 0.8024 1.3068 -0.2957 0.4803 0.8194
0.3258 0.8258 0.0306 1.1121 1.1427 -0.7694 0.6228 0.6561
>> r=corrcoef(x)
r =
1.0000 1.0000 0.1033 -0.1638 -0.0395 0.1033 -0.7095 -0.0109
1.0000 1.0000 0.1033 -0.1638 -0.0395 0.1033 -0.7095 -0.0109
0.1033 0.1033 1.0000 -0.1673 0.6767 1.0000 -0.1251 0.8443
-0.1638 -0.1638 -0.1673 1.0000 0.6127 -0.1673 0.0237 -0.2586
-0.0395 -0.0395 0.6767 0.6127 1.0000 0.6767 -0.0826 0.4837
0.1033 0.1033 1.0000 -0.1673 0.6767 1.0000 -0.1251 0.8443
-0.7095 -0.7095 -0.1251 0.0237 -0.0826 -0.1251 1.0000 0.1263
-0.0109 -0.0109 0.8443 -0.2586 0.4837 0.8443 0.1263 1.0000
>> [i]=r>0.5
i =
1 1 0 0 0 0 0 0
1 1 0 0 0 0 0 0
0 0 1 0 1 1 0 1
0 0 0 1 1 0 0 0
0 0 1 1 1 1 0 0
0 0 1 0 1 1 0 1
0 0 0 0 0 0 1 0
0 0 1 0 0 1 0 1
>> q=cov(r)
q =
0.3354 0.3354 -0.0082 -0.0970 -0.0790 -0.0082 -0.2943 -0.0584
0.3354 0.3354 -0.0082 -0.0970 -0.0790 -0.0082 -0.2943 -0.0584
-0.0082 -0.0082 0.2515 -0.0928 0.1323 0.2515 -0.0310 0.2271
-0.0970 -0.0970 -0.0928 0.2126 0.0844 -0.0928 0.0417 -0.1095
-0.0790 -0.0790 0.1323 0.0844 0.1691 0.1323 0.0064 0.1002
-0.0082 -0.0082 0.2515 -0.0928 0.1323 0.2515 -0.0310 0.2271
-0.2943 -0.2943 -0.0310 0.0417 0.0064 -0.0310 0.2880 0.0340
-0.0584 -0.0584 0.2271 -0.1095 0.1002 0.2271 0.0340 0.2291
>> p=inv(q)
Warning: Matrix is close to singular or badly scaled.
Results may be inaccurate. RCOND = 2.001513e-019.
p =
1.0e+018 *
1.5339 -1.5339 -0.1557 -0.3053 0.4089 -0.1720 -0.0000 -0.0000
-1.5339 1.5339 0.1557 0.3053 -0.4089 0.1720 0.0000 0.0000
-0.1557 0.1557 0.0024 0.0098 -0.0131 0.0082 0.0000 0.0000
-0.3053 0.3053 0.0098 0.0408 -0.0546 0.0340 0.0000 0.0000
0.4089 -0.4089 -0.0131 -0.0546 0.0731 -0.0455 -0.0000 -0.0000
-0.1720 0.1720 0.0082 0.0340 -0.0455 0.0283 0.0000 0.0000
-0.0000 0.0000 0.0000 0.0000 -0.0000 0.0000 0.0000 -0.0000
-0.0000 0.0000 0.0000 0.0000 -0.0000 0.0000 -0.0000 0.0000
>> [j]=p>0.5
j =
1 0 0 0 1 0 0 0
0 1 1 1 0 1 1 1
0 1 1 1 0 1 1 1
0 1 1 1 0 1 1 1
1 0 0 0 1 0 0 0
0 1 1 1 0 1 1 1
0 1 1 1 0 1 1 0
0 1 1 1 0 1 0 1
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