R中的对应分析

我正在尝试使用ca库在R中运行对应分析，但出现以下错误：

Error in svd(S) : infinite or missing values in 'x'

此外：警告消息：

sqrt（eP）中的

这是我的数据集

                  Dif_Aud Dif_Alc Dif_Shr     Dif_Ats
DKIDS              -17307 -105249   0.361 -2.26666666
CARTOON            -14583 -132158   0.430  2.16666666
SPORTV             -23820 -208902  -0.796 -1.53333333
MULTISHOW            3869  -30392   1.770  4.61666667
MEGAPIX            -11683 -129625   0.086 -0.43333333
FOX                -25429 -185373  -1.413 -7.56666666
TNT                -12390 -116205  -0.250 -3.75000000
SPACE               -7121  -89169   0.164 -0.43333333
VIVA                -4720  -75378   0.390  0.86666667
DISNEY             -14668  -96903  -0.644 -7.95000000
TC PREMIUM            675   25897   0.837 -1.98333333
UNIVERSAL          -12952 -104380  -0.569 -6.55000000
TC PIPOCA            2017   51298   0.934 -4.30000000
AXN                 -6406  -60997   0.062 -0.90000000
DISCOVERY CHANNEL   -7080  -86041  -0.029 -1.60000000
GNEWS               -2457  -89800   0.408  4.76666667
FX                 -12896 -143305  -0.663 -2.13333334
GNT                 -1915  -75992   0.365  4.31666666
TC ACTION             103   13328   0.544 -2.25000000
NICK                -5392  -61935  -0.018 -0.06666666
SPORTV_2            -4223  -83112   0.085  0.55000000
WARNER              -6717  -68173  -0.218 -4.10000000
H&H                 -9809 -119686  -0.550  1.53333333
ANIMAL               1172  -21680   0.507  5.35000000
NATGEO              -7404 -127921  -0.356 -1.10000000
ESPN BR             -2676  -18278   0.060 -4.20000000
CINEMAX             -5028  -96745  -0.180 -0.68333333
FOX SPORTS         -10027  -73034  -0.709 -7.33333333
SONY                -3979  -58269  -0.118 -2.25000000
HISTORY             -8792 -110035  -0.608 -4.10000000
BOOMERANG           -5084  -62047  -0.253 -0.93333334
TC FUN              -3711  -36152  -0.129 -4.98333333
HBO                  1088   22788   0.317  1.28333334
SPORTV 3            -2948  -95394  -0.093  0.68333334
FOX Life            -2286  -52071  -0.034  5.83333334
GLOOB               -6703  -73867  -0.482 -6.26666667
TLC                 -5305  -75255  -0.352 -2.90000000
DISNEY XD           -4517  -51180  -0.292 -5.06666667
A&E                 -4565  -84667  -0.306  0.26666667
MTV                 -4399  -67367  -0.325 -2.48333334

当我在这个对象中运行svd时

> svd(analise)
$d
[1] 586218.63825  21265.02168     37.52027     16.15292      2.09432

$u
             [,1]        [,2]         [,3]        [,4]         [,5]
 [1,]  0.18150580 -0.35027170  0.121797235  0.20447594  0.384868406
 [2,]  0.22677778 -0.10510095  0.143836533  0.28852816  0.284867160
 [3,]  0.35858927 -0.20212370  0.138182724  0.21491424 -0.139866059
 [4,]  0.05100616  0.31400723  0.171410051 -0.02997187  0.540177937
 [5,]  0.22201573  0.01961012  0.078690335  0.04468443  0.116447686
 [6,]  0.31888129 -0.38031298  0.096648971 -0.01609187 -0.312133863
 [7,]  0.19933447 -0.07215610  0.042661241 -0.08183358  0.031594719
 [8,]  0.15257935  0.05636619  0.097778029 -0.03556821  0.066439422
 [9,]  0.12877513  0.10850103  0.112478175 -0.01871585  0.112140330
[10,]  0.16691197 -0.26319170 -0.009717159 -0.17637196 -0.016410347
[11,] -0.04409211 -0.08159895  0.275621286 -0.21061595  0.161254500
[12,]  0.17933927 -0.15016090 -0.044239995 -0.16177399 -0.004591287
[13,] -0.08744755 -0.12979959  0.281822798 -0.34298422  0.203065145
[14,]  0.10461689 -0.03330469  0.041209263  0.01183071  0.086216607
[15,]  0.14726006  0.04461236 -0.012883596 -0.04962331  0.082898454
[16,]  0.15291151  0.27750226  0.085394175  0.10865458  0.061302591
[17,]  0.24544303  0.02261448 -0.131671500  0.04754004 -0.026167394
[18,]  0.12937320  0.24252074  0.184695518  0.04960557 -0.048427775
[19,] -0.02265344 -0.05343815  0.198548356 -0.20309772  0.093648877
[20,]  0.10604926  0.01827305 -0.067679470  0.07265230  0.120310236
[21,]  0.14183223  0.16557921  0.026622370 -0.03989230  0.025396062
[22,]  0.11685437 -0.01649793 -0.052915136 -0.15331633  0.047792910
[23,]  0.20483755  0.06390800 -0.134978543  0.22219876 -0.029791010
[24,]  0.03663682  0.14964563  0.380769937  0.04887125 -0.181505291
[25,]  0.21844303  0.21251250 -0.092643024 -0.08459933 -0.041012944
[26,]  0.03146882 -0.04539684  0.128353670 -0.26946049 -0.033165280
[27,]  0.16511501  0.18748156 -0.001570025 -0.11028449 -0.067216665
[28,]  0.12563546 -0.15022985 -0.251560894 -0.14310074  0.085496472
[29,]  0.09959864  0.06840724  0.039239453 -0.16328892 -0.053525914
[30,]  0.18828443  0.06933826 -0.146343748 -0.14252305 -0.047378800
[31,]  0.10619065  0.03318379 -0.023171971 -0.01634178 -0.039357164
[32,]  0.06199126 -0.01572483  0.025775411 -0.27846041 -0.020303504
[33,] -0.03887708 -0.04867093  0.444702495 -0.11073835 -0.267501226
[34,]  0.16249057  0.27896568  0.092346466 -0.14899540 -0.168317704
[35,]  0.08880311  0.12058372  0.199176919  0.22020238 -0.219093227
[36,]  0.12652320  0.00904771 -0.196233272 -0.23869870  0.053669639
[37,]  0.12865898  0.08057232 -0.112181262 -0.12636002 -0.008495483
[38,]  0.08764355  0.01222865 -0.152791143 -0.20826849  0.071518275
[39,]  0.14452757  0.15636344 -0.103095883  0.01313241 -0.032957984
[40,]  0.11511785  0.08851215 -0.064381624 -0.13734630 -0.055181864

$v
              [,1]          [,2]          [,3]          [,4]          [,5]
[1,] -2.161539e-05  1.969082e-04  9.783142e-01 -2.007724e-01 -5.090993e-02
[2,] -9.295601e-02  9.956700e-01 -3.248368e-04 -5.870256e-04 -3.671252e-05
[3,] -9.956702e-01 -9.295601e-02  5.866027e-06  4.406851e-05  2.142571e-06
[4,] -2.624744e-06  5.694367e-05  5.303213e-02  5.202400e-03  9.985793e-01
[5,] -1.532831e-05  6.408762e-04  2.002221e-01  9.796239e-01 -1.573699e-02

然后dput

dput(analise)
structure(list(Dif_Aud = c(-17307, 
-14583, -23820, 3869, -11683, -25429, -12390, -7121, -4720, -14668, 
675, -12952, 2017, -6406, -7080, -2457, -12896, -1915, 103, -5392, 
-4223, -6717, -9809, 1172, -7404, -2676, -5028, -10027, -3979, 
-8792, -5084, -3711, 1088, -2948, -2286, -6703, -5305, -4517, 
-4565, -4399), Dif_Alc = c(-105249, -132158, -208902, -30392, 
-129625, -185373, -116205, -89169, -75378, -96903, 25897, -104380, 
51298, -60997, -86041, -89800, -143305, -75992, 13328, -61935, 
-83112, -68173, -119686, -21680, -127921, -18278, -96745, -73034, 
-58269, -110035, -62047, -36152, 22788, -95394, -52071, -73867, 
-75255, -51180, -84667, -67367), Dif_Shr = c(0.361, 0.43, -0.796, 
1.77, 0.0860000000000003, -1.413, -0.25, 0.164, 0.39, -0.644, 
0.837, -0.569, 0.934, 0.0620000000000003, -0.0289999999999999, 
0.408, -0.663, 0.365, 0.544, -0.018, 0.085, -0.218, -0.55, 0.507, 
-0.356, 0.0600000000000001, -0.18, -0.709, -0.118, -0.608, -0.253, 
-0.129, 0.317, -0.093, -0.034, -0.482, -0.352, -0.292, -0.306, 
-0.325), Dif_Ats = c(-2.26666666000001, 2.16666666, -1.53333333, 
4.61666667, -0.43333333, -7.56666666, -3.75, -0.43333333, 0.866666670000001, 
-7.95, -1.98333333, -6.55, -4.3, -0.899999999999999, -1.6, 4.76666667, 
-2.13333334, 4.31666666, -2.25, -0.0666666599999992, 0.550000000000001, 
-4.1, 1.53333333, 5.35, -1.1, -4.2, -0.68333333, -7.33333333, 
-2.25, -4.1, -0.933333340000001, -4.98333333, 1.28333334, 0.683333340000001, 
5.83333334, -6.26666667, -2.9, -5.06666667, 0.266666669999999, 
-2.48333334)), .Names = c("Dif_Aud", "Dif_Alc", "Dif_Shr", 
"Dif_Ats"), row.names = c("DKIDS", "CARTOON", "SPORTV", "MULTISHOW", 
"MEGAPIX", "FOX", "TNT", "SPACE", "VIVA", "DISNEY", "TC PREMIUM", 
"UNIVERSAL", "TC PIPOCA", "AXN", "DISCOVERY CHANNEL", "GNEWS", 
"FX", "GNT", "TC ACTION", "NICK", "SPORTV_2", "WARNER", "H&H", 
"ANIMAL", "NATGEO", "ESPN BR", "CINEMAX", "FOX SPORTS", "SONY", 
"HISTORY", "BOOMERANG", "TC FUN", "HBO", "SPORTV 3", "FOX Life", 
"GLOOB", "TLC", "DISNEY XD", "A&E", "MTV"), class = "data.frame")

有人知道可能会出什么问题吗

谢谢
您不能对具有负值的数据（如显示的数据集）执行CA。最初的方法用于非负频率/计数数据，如列联表中的数据

例如，我们不允许CA适用于素食者包中具有非正行和的数据。同样，列总和必须为正。因此，总和也需要是正的，这三个总和被用来作为CA的一部分对数据进行加权

您的数据显然不符合该方法的要求

相反，考虑PCA，尽管你需要对输入数据进行标准化，否则大值的变量会倾向于支配排序，因为它们倾向于有较大的差异。
你能显示一些你称之为SVD的代码吗？那么这个例子中的eP是什么呢？谢谢你的关注，@Cleb。我不知道eP是什么。调用svd后，我用代码编辑了原始帖子。
svd（analise）
的结果没有帮助，我们不知道analise是什么。你能发布dput吗？“analise”是数据集我对对应分析不太了解，但它看起来像是针对频率数据的，而这显然不是？事实上，
sum（analise）
是负数，这把一切都搞砸了。注
ca（abs（analise））
工作正常。