我有一个矩阵，其时间序列包含23个元素（Var01-Var23），增长和年份（参见下面的数据）。 然后，我想知道哪一组化学元素阻止了我树木的生长。
当我将每个单独的元素与growth变量相关联时，结果非常低。但是当我计算所有元素的mean并将其与growth变量相关联时，相关性会增加。或者当我将增长与mean个选定元素相关联时，相关性会增加（例如，Var02，Var04和Var09的平均值为Var13）。我有几棵树的数据，然后我需要一些脚本来自动计算，因为目前我正在以手动方式进行。
# Example:
# My data
data <- read.delim("clipboard")
# Correlation with Mean of all variables (r= -0.64)
cor.test(data$growth, rowMeans(data[,3:25]))
# Correlation with Mean of seven variables (r= -0.65)
cor.test(data$growth, rowMeans(data[,c(4,6,11:15)]))
基于PCA和分层聚类分析，我正在计算一些元素的growth和mean之间的相关性（包含所有可能的元素组合）。此时，当我添加一个或多个元素时，我的相关性增加了o，反之亦然。另外，我将growth与所有变量相关联，我只选择了第一个高相关元素，但这并不是我想要的。
我想知道元素的精确组合与growth变量具有最高的相关性。
我已经看到strip.rwl()包的函数dplR进行了类似的计算。此功能会丢弃所有时间序列，这些时间序列无助于改善某种类型的相关性（EPS）。此函数为您提供具有最高序列间相关性的精确变量。
类似，但我想知道变量的精确组合是什么，这些变量能够让我得到最好的mean来计算与增长的最高相关性？
是否已经有计算这个的功能，或者你可以给我一些方向吗？
数据：
year growth var01 var02 var03 var04 var05 var06 var07 var08 var09 var10 var11 var12 var13 var14 var15 var16 var17 var18 var19 var20 var21 var22 var23
2015 0.7355 -1.5093 -0.4718 0.4724 -1.2182 1.2762 2.1297 -0.3869 2.5204 0.5939 0.4910 -0.6156 -0.7688 -0.7586 -1.3430 2.0780 -1.5219 -1.2929 -0.6673 -1.2759 -1.3003 -1.1383 -1.0050 -1.0538
2014 1.0499 -1.5731 -0.8291 0.3671 -1.2009 1.2957 1.5425 -0.5630 1.3536 1.9637 0.4473 -0.5620 -0.6266 -0.6508 -1.4364 1.5605 -1.6061 -0.9849 -0.4060 -1.4001 -0.5928 -0.9355 -0.9086 -1.1744
2013 0.3023 -1.3480 -0.9086 1.0562 -1.4676 1.6038 1.6197 -0.9654 0.8675 -0.5802 0.3953 -0.6743 -1.2814 -0.9289 -1.7962 1.6508 -1.6769 -1.2483 -0.4202 -1.7725 -0.5117 -0.8456 -1.1292 -1.1822
2012 0.4691 -1.4137 -1.3467 0.8196 -0.9280 1.5524 1.6472 -0.6955 1.2168 0.3453 0.4625 -0.4587 -0.8154 -0.4288 -1.8088 1.5263 -1.5974 -1.2437 -0.6041 -1.9023 -0.4178 -0.7794 -1.0962 -1.4127
2011 1.5789 -1.3981 -0.9584 1.1080 -1.5778 1.3515 1.4592 -1.2458 1.2315 -0.8985 0.3111 -0.7732 -1.5045 -1.3703 -1.8152 1.4385 -1.5522 -1.3145 -0.5637 -1.7576 -0.8766 -1.0122 -1.5530 -1.3255
2010 1.2607 -1.3424 -0.8443 1.1052 -1.1118 1.3660 1.3892 -1.0938 1.2785 -0.9152 0.3842 -0.4285 -0.5272 -0.5904 -1.7213 1.4067 -1.4321 -0.2067 -0.3469 -1.7433 -0.1480 -0.2845 -0.7672 0.7892
2009 -0.5909 -0.7340 -0.5030 0.1297 -0.9245 1.3174 1.2938 -0.4455 1.0780 -0.5008 0.3727 -0.3743 -0.6238 -0.6003 -1.8261 1.3141 -0.9217 -0.3761 -0.4310 -1.8382 -0.3053 -0.5241 -0.7800 0.2114
2008 -0.6983 -1.1673 -0.1231 0.5825 -1.2651 1.6569 1.3955 -0.7211 0.9760 -0.7845 0.3861 0.0815 -0.3776 -0.6394 -1.7565 1.4102 -1.1523 -0.4078 -0.3300 -1.8786 -0.4062 -0.4016 -0.4600 -0.0071
2007 0.1183 -1.3682 -0.9443 -0.0971 -1.3220 1.3293 1.2750 -0.8371 1.0943 -1.0089 0.3398 -0.4498 -1.2298 -1.2716 -1.6478 1.3486 -1.3283 -0.7784 -0.2968 -1.5428 -0.1280 -0.7084 -0.9944 -0.5956
2006 0.5534 -1.2314 -0.7071 -0.7115 -1.2178 1.0437 1.1603 -0.8700 1.0272 -0.7154 0.3785 -0.7280 -0.8290 -0.7931 -1.4326 1.2680 -1.2664 -1.1744 -0.3001 -1.2794 -0.2198 -0.3347 -0.7982 -0.8576
2005 -0.1290 -0.6186 -0.7554 -0.8953 -0.7179 0.8193 1.2671 0.0563 1.1459 -0.3939 0.5788 -0.4018 -0.4051 -0.0909 -0.3482 1.1628 -0.6649 -0.5135 -0.1499 -0.5293 1.7077 1.3397 -0.5928 -0.3255
2004 -1.3960 -0.7433 3.3826 0.0168 0.6878 2.3632 2.0095 1.4930 1.1984 1.6115 0.9325 6.0082 3.4345 4.0293 -0.7450 1.8678 -1.1456 1.7131 -0.0351 -0.8672 -1.1172 0.6631 1.9708 1.3615
2003 -1.2024 -1.1421 1.4662 0.1289 -0.2702 1.5784 1.8177 0.4645 1.0738 0.3043 0.6369 0.1920 0.5853 0.6188 -0.9899 1.7807 -1.1835 0.8453 -0.3640 -0.8570 -0.2409 -0.7386 0.7062 0.1594
2002 -1.2695 -1.2228 -0.7048 -0.5232 -0.6171 1.9463 1.6148 0.2365 0.7777 1.1024 0.6519 0.3360 0.8234 0.8263 -0.7476 1.6094 -1.3752 1.7203 -0.2869 -0.9334 0.3433 0.2585 0.9249 0.3958
2001 2.2805 -2.0591 -0.8628 -3.9804 -1.5726 0.1381 0.5142 -0.6226 0.3808 -1.2949 0.7876 -0.5202 -0.4475 -0.2446 -1.7901 0.7399 -2.4933 0.4975 0.3481 -1.8721 2.6124 2.2446 -0.6788 0.8185
2000 1.2243 -0.3546 -0.3555 -0.9080 0.6723 0.7487 1.2527 0.2992 1.7156 1.4165 2.3882 -0.1943 -0.5190 -0.0279 -0.9017 1.3534 -0.8618 -0.0725 1.9422 -0.8831 2.9700 2.1966 -0.3275 0.5609
1999 1.1170 -1.0957 -0.5224 -0.9462 -0.8757 0.8819 1.2233 -0.1417 1.4077 0.3444 0.7656 -0.5936 -0.5658 -0.5246 1.7319 1.2449 -0.9524 0.1268 0.5618 1.6841 2.6959 2.1735 -0.6886 -0.0353
1998 1.5080 -0.9427 -0.5292 -1.9068 -0.9694 0.5602 0.9686 -0.5317 0.9646 -0.5927 0.5123 -0.5573 -0.6479 -0.6202 -1.2297 1.1412 -1.0400 -0.3132 -0.1830 -1.1215 2.2558 2.0275 -0.7357 -0.2513
1997 1.2109 -1.2957 -0.2941 -1.7398 -0.4912 0.4444 0.7539 -0.4458 0.7561 -0.3942 0.4130 -0.6011 -0.5307 -0.1443 -1.0119 0.8553 -1.2888 -1.1635 -0.2902 -1.0984 -0.3384 -0.7099 -0.7028 -0.6451
1996 1.9374 -0.9590 -0.5634 -1.1346 -0.8146 0.1582 0.5529 -0.7560 0.3428 -0.7315 0.3842 -0.9918 -1.1590 -0.8275 -1.0101 0.6369 -0.9615 -1.1021 -0.2902 -1.0126 -0.3163 -0.3251 -1.0070 -0.8537
1995 -0.0906 -0.6876 -0.5482 -0.7573 -0.8502 0.0115 0.3705 -0.8278 0.3808 -0.4898 0.4215 -0.7297 -0.9322 -0.9299 -0.4233 0.2834 -0.5797 -0.7969 0.0192 -0.4001 -0.0401 -0.2343 -0.8086 -0.4427
1994 -0.6005 -0.0975 -0.6942 -0.5902 -0.0880 0.3175 0.1632 0.7675 0.5207 1.0282 0.5350 0.0978 0.7515 0.6528 0.2238 0.1230 0.0881 -0.4784 0.2601 0.2429 0.1688 0.1807 0.9592 0.0418
1993 -0.6331 -0.1956 0.0405 -0.8816 -0.7516 -0.2010 -0.1611 -0.4313 0.3369 1.1248 0.4827 -0.8354 -0.7042 -0.9057 0.2060 -0.1867 0.1458 -0.7784 -0.0915 0.3305 -0.0211 -0.3948 -0.2624 -0.1793
1992 -1.4688 0.9073 3.1301 0.8338 2.5185 1.8601 0.5797 2.6687 1.9719 4.6638 1.2484 2.0706 2.6003 2.8108 1.4070 0.3997 0.9439 2.4897 1.1890 1.3518 1.0730 0.8020 3.1918 2.0749
1991 0.1202 -0.0531 -0.0162 0.0803 -0.1292 -0.2617 0.1123 -0.2343 0.1041 0.1202 0.5609 -0.2215 0.2995 0.3069 0.1439 0.1829 0.2389 1.6160 -0.0490 0.4088 0.8250 -0.1432 0.4282 2.4041
1990 0.7739 0.1974 -0.2758 -0.2005 -0.4915 -0.4294 -0.1930 -0.3400 -0.1200 -0.6279 0.4248 -0.5160 -0.3597 -0.2878 0.1752 -0.2011 0.5998 -0.2399 -0.3001 0.3875 0.4752 -0.2927 -0.4844 0.4067
1989 1.4409 -0.1443 -0.4217 -0.7657 -1.0045 -1.0412 -0.4217 -0.8033 -0.1983 -0.6299 0.4042 -0.6739 -0.4189 -0.2231 -0.0075 -0.4847 0.1006 -1.2786 -0.2707 0.0786 -0.0884 -0.3562 -0.5116 -0.9430
1988 0.0627 0.0790 -0.3464 -0.9041 -1.0201 -0.6182 -0.5480 -0.4564 -0.2100 -0.9290 0.4112 -0.8355 -0.7661 -0.8463 0.1953 -0.5956 0.2049 -0.5149 0.0899 0.2429 0.2949 -0.3993 -0.4629 -1.6034
1987 -0.0772 0.3881 -0.1524 -0.5225 0.1709 -0.6857 -0.4846 0.3772 -0.2441 0.0915 -0.7341 -0.1923 0.1421 1.1470 0.5189 -0.6089 0.6509 0.1051 -0.1116 0.5543 -0.3053 0.2307 -0.0151 1.7381
1986 0.9272 0.1445 -0.0866 -0.5388 -0.2163 -0.9456 -0.5572 -0.6548 -0.2948 -1.0206 -0.9377 -0.5081 -0.0798 -0.4386 0.3222 -0.6297 0.4495 -0.5263 -0.2200 0.2290 -1.2341 -0.6906 -0.2357 0.2041
1985 1.1131 0.0253 -0.4906 -0.5509 -0.2975 -0.9225 -0.6997 -0.6370 -0.0884 -0.3245 -1.1308 -0.7209 -0.8256 -0.9482 0.2401 -0.7110 0.2473 -0.7735 -0.4202 0.3121 -1.2059 -0.7069 -0.8015 -0.2975
1984 1.8013 0.2284 -0.5440 -0.1447 -0.4211 -0.8235 -0.6575 -0.7925 -0.1492 -0.9069 -1.1281 -0.7848 -0.6862 -0.7732 0.4834 -0.6695 0.5650 -1.0714 -0.4167 0.4992 -0.8736 -0.3715 -0.8133 -0.7442
1983 0.9502 0.0912 -0.3639 -0.6158 -0.3501 -0.8718 -0.7431 -0.8826 -0.8025 -1.1922 -1.1150 -0.4250 0.2337 -0.0468 0.4108 -0.7577 0.3113 -0.5710 -0.3989 0.3311 -1.8749 -1.9467 0.0756 -0.6873
1982 -0.9436 0.9775 0.7716 0.2479 0.9319 -0.1762 -0.6461 -0.1360 -1.8662 -0.3247 -1.1207 -0.1339 1.3616 0.7641 0.7340 -0.7842 0.7577 1.3445 -0.4060 0.5994 0.1340 0.3584 1.7261 0.3133
1981 -0.9666 0.4902 -0.6478 -0.4053 0.9247 -0.2615 -0.8484 -0.2314 -1.6397 -0.8245 -1.3230 0.5140 1.0220 1.1154 0.6691 -0.8737 0.4194 0.8998 -0.7992 0.5904 0.1163 0.3389 0.8467 -0.1124
1980 -1.2541 1.7357 1.7745 1.7795 1.6191 0.5960 -0.7116 1.6093 -1.5534 0.7996 -0.6887 1.5322 2.6049 2.8926 1.2064 -0.6855 1.1873 1.7319 -0.0972 1.1336 0.1602 0.3776 2.4082 0.2887
1979 0.9234 0.3475 -0.4153 -0.5224 0.1081 -0.8532 -0.9357 -0.0814 -0.5229 -1.0353 -1.0966 -0.1029 0.0437 -0.0171 0.4097 -0.7625 0.3251 1.0325 -0.3744 0.3936 -0.8812 -0.3848 -0.2112 2.3548
1978 0.5477 0.3268 -0.4658 -0.4173 -0.2025 -0.9164 -0.8704 -0.6012 -0.4608 -1.0767 -0.9210 -0.3823 -0.1133 -0.5651 0.3620 -0.7968 0.4289 -0.2014 -0.2075 0.4020 -1.1600 -0.8439 -0.2556 0.4952
1977 0.2065 0.4730 -0.1826 0.0941 -0.1233 -0.9184 -0.7367 -0.0390 -0.6020 -0.5310 -0.8984 0.0119 0.1358 0.2026 0.7328 -0.7439 0.6711 -0.1219 -0.1921 0.7615 -0.4529 -0.1719 -0.1456 0.0670
1976 0.9004 0.3434 -0.3918 0.7682 0.1170 -0.7074 -0.5424 -0.7441 -0.1253 -0.0578 -1.0464 -0.4098 -0.9362 0.0920 1.0475 -0.7216 0.9563 -0.6707 -0.3166 0.8140 -0.5776 -0.0814 -0.7861 -0.4623
1975 0.6972 0.1800 -0.8167 0.1120 -0.1196 -0.8904 -0.8327 -0.1215 -0.4762 -0.4726 0.3593 -0.3703 -0.2568 -0.2583 0.7316 -0.8034 0.5018 -1.0593 -0.5518 0.6697 -1.2341 -0.7069 -0.5976 -0.8553
1974 -1.2120 1.1185 1.5724 0.8716 0.7787 0.1795 -0.8420 0.6933 -1.9117 0.0430 -1.2172 0.1498 -0.1294 -0.4590 1.3863 -0.7974 1.0743 1.1988 -0.5597 1.3714 0.9767 1.0511 0.4705 0.4016
1973 -0.9628 0.4276 -0.0410 0.1087 0.2920 -0.2293 -0.9448 -0.2077 -1.0053 -0.5260 -0.9422 -0.1569 -0.8008 -0.5443 0.4898 -0.8743 0.4793 -0.7277 -0.2231 0.5532 0.1515 0.3713 -0.4173 -0.1950
1972 -0.3417 0.5028 -0.0892 0.1256 0.2009 -0.8769 -0.9136 -0.4308 -1.1777 -0.5572 -1.3502 0.0552 0.2952 -0.0647 0.4340 -0.8732 0.5752 -0.7586 -0.8786 0.4637 0.1074 0.3324 0.1065 -0.7151
1971 -1.0663 1.4514 0.7596 1.0064 1.4265 -0.1857 -0.6966 0.0646 -1.5851 -0.1682 -0.9928 0.8045 1.2418 1.5867 1.0944 -0.7248 1.0222 0.3959 -0.2643 1.1645 0.1427 0.3649 1.0996 -0.4215
1970 -0.1731 0.2830 -0.2867 0.3696 0.1652 -0.7090 -0.8112 -0.3736 -0.3142 -0.5996 0.4910 0.0731 -0.0576 0.2005 0.6857 -0.6739 0.5739 1.4645 0.1127 0.8136 -0.9955 -0.3454 -0.2405 2.7218
1969 0.5496 0.0708 -1.1229 -0.2215 -0.0224 -1.1272 -1.0123 -0.2998 0.0002 0.7823 -1.2852 -0.4108 -0.6424 -0.0993 0.4756 -0.9020 0.2522 0.0435 -0.7023 0.4398 -1.7905 -1.7240 -0.7576 0.4713
1968 0.4557 0.3754 -0.1914 0.0782 -0.0442 -1.0424 -0.8591 -0.5058 -0.0528 -0.6357 -0.8632 -0.2303 -0.0315 -0.4494 0.8054 -0.8174 0.4188 -0.1702 -0.1709 0.8400 0.1515 0.3713 -0.0779 0.1860
1967 -0.0331 0.4082 -0.1135 0.3716 0.3029 -0.8140 -0.8333 -0.3632 -0.3441 -0.6185 -0.8795 -0.0115 0.4341 -0.2016 0.5365 -0.8199 0.6325 0.4662 -0.1799 0.5568 0.1515 0.3713 0.3658 0.0823
1966 -1.3091 2.4265 1.9120 3.5159 1.7204 0.3925 -0.3358 4.0710 -1.1894 1.1428 -0.7170 1.0888 2.2487 1.3671 1.8517 -0.4379 2.4150 2.5052 -0.1059 1.8671 0.1602 0.3776 2.4620 1.4373
1965 -0.3865 0.6265 0.4303 0.2184 0.2952 -0.5675 -0.8397 -0.5385 -0.4155 0.8830 0.1583 0.2678 0.6830 0.5453 0.7177 -0.8522 0.7218 0.2577 -0.0269 0.6639 0.1688 0.3840 0.4992 -0.2566
1964 0.0761 0.2908 -0.2917 0.0262 0.8445 -0.8938 -0.9006 -0.4216 -0.4443 0.3291 -0.7933 -0.2331 0.0098 -0.4144 0.2669 -0.7975 0.4580 -0.4564 -0.1351 0.3079 -1.7992 -4.0357 -0.1313 -0.7129
1963 -0.5091 0.3587 -0.3000 0.2313 0.6458 -0.8484 -0.8979 0.2260 -0.5598 0.7006 -0.9991 -0.1602 -0.2566 -0.6252 0.3226 -0.9419 0.5258 0.0035 -0.2707 0.2862 0.1427 0.3649 -0.1694 -1.1526
1962 -1.1161 0.7858 0.1291 0.9148 0.5731 -0.5193 -0.7648 0.1396 -0.5341 0.1245 -1.0139 1.0248 0.4818 0.6698 0.7706 -0.7147 0.9169 0.3912 -0.2837 0.8386 0.1427 0.3642 0.2324 -1.1177
1961 -0.9015 0.5666 0.1987 0.3679 0.9936 -0.8241 -0.7050 0.9734 -0.6841 0.1911 -1.0430 0.0148 0.1850 -0.2893 0.4734 -0.8045 0.6152 -0.3412 -0.3133 0.3074 0.1427 0.3649 0.1296 -1.4248
1960 -1.0433 0.5102 0.4145 0.5807 0.9967 -0.7398 -0.7065 1.4128 -0.4794 1.3586 0.5110 -0.0877 -0.4572 -0.5883 0.6178 -0.6754 0.7916 0.3395 0.1253 0.5598 -0.2515 0.0197 -0.2512 2.0852
1959 -0.8593 0.4067 -0.3155 0.3043 0.1448 -0.9809 -0.7874 0.0866 -0.6011 -0.3097 -0.8248 -0.2912 -0.7388 -0.0724 0.3642 -0.7552 0.6715 -0.2708 -0.1499 0.3971 0.1515 0.3713 -0.4288 0.4693
1958 -1.3883 1.4330 0.6080 0.7613 2.0997 -0.0061 -0.8815 0.6944 -0.7064 1.4439 0.4042 0.3192 0.0227 -0.1728 1.2644 -0.7873 1.5796 0.5583 0.5341 1.2738 0.2201 0.4340 0.4769 0.8129
1957 -0.1501 0.0788 -0.6378 0.5301 -0.0052 -1.4811 -0.7726 -0.5773 -0.1142 -0.3035 0.3192 -0.3458 -0.2647 -0.3562 0.4415 -0.8422 0.7440 -1.1722 0.0219 0.2437 0.1688 0.3840 -0.4811 -0.7914
1956 -1.1660 0.9024 0.9387 -0.4486 0.7415 -0.7435 -0.9087 0.5561 -1.5628 -0.0826 3.3428 0.8977 0.0357 -0.6959 0.0996 -0.8731 0.1990 1.3175 5.4730 -0.0201 1.4525 1.4838 0.7398 0.2129
1955 -1.2810 2.6427 3.0556 1.7682 2.6251 -0.2087 -0.3884 2.1850 -1.2176 1.1117 2.8520 1.7799 2.3472 1.9516 0.9034 -0.6220 1.4277 1.9119 4.3493 1.1407 1.0612 1.1603 2.8571 0.6604
1954 -0.9513 1.7707 1.0759 -0.4117 1.8763 -0.7741 -0.9430 2.8715 -0.9605 0.0427 0.9580 0.7628 -0.5342 0.0212 -0.2429 -0.9756 0.4455 0.4704 0.5851 -0.1011 0.2286 0.4340 0.1032 -0.4706
1953 -0.7213 0.3247 0.8136 -0.1111 0.2263 -1.6928 -0.7778 0.1082 -0.5078 -0.6086 -0.8420 0.6116 0.8281 -0.0156 0.0789 -0.8039 0.2684 -0.2745 -0.1588 -0.0194 0.1515 0.3713 0.7915 -0.9210
答案 0 :(得分：2)
首先，有23个变量，你有8,388,607种可能的组合（2 ^ 23 - 1）。可能你不想去那里。
你可以做的是尝试找到一种能让你获得更好和更好组合的算法。我依靠stepwise regression中反向消除背后的逻辑来做到这一点。基本上，我从所有变量的行方式开始，然后一次丢弃一个变量，计算每个n-1组合的行均值和相关性，然后选择最好的一个并重新完成整个事情：看看所有潜在的n-2组合，计算相关性等。你已经有了这个想法。
现在，无法保证这可以找到最佳组合，但结果（r = -0.76）是一项重大改进。
如果您尝试向前选择会发生什么，那将会很有趣。
以下是代码：
vars <- data[,-1:-2] #create data frame with only the variables in it
best <- NA # stores the best correlation in any given iteration
var_names <- NULL #stores variables in the given iteration
while(ncol(vars) > 2 ){
temp_mean <- NULL #stores rowmeans
temp_cor <- NULL #stores correlations
var_names <- c(var_names, list(names(vars))) #updates list with variable names
for(i in 1:ncol(vars)){
low_vars <- vars[,-i] #drop each variable one-by-one
temp_mean <- rowMeans(low_vars[,1:ncol(low_vars)]) #calculate means
temp_cor <- c(temp_cor, cor(temp_mean, data$growth)) #calculate correlation
}
best <- c(best, min(temp_cor)) #best correlation of given iteration stored
vars <- vars[, -which.min(temp_cor)] #update vars to best combination
}
min(best, na.rm = T) #check what is the best correlation found
var_names[[which.min(best)]] #check what combination lead to it