抱歉，我是stats和r的新手，所以我的术语可能不对。我试图通过链式鼠标进行链式方程式的多重插补。
当我运行它时，我立即得到错误：
'cor中的错误（xobs [，keep，drop = FALSE]，use =“all.obs”）：'x'是 空“
我已经尝试删除有问题的变量，但是当进程到达下一个缺少数据的变量时，错误就会跳起来。等等。 我非常感谢任何帮助或见解。谢谢！
我希望这是数据的相关格式：
structure(list(V1_A = c("Nama", "Kung", "Thonga", "Lozi", "Mbundu",
"Suku"), ord = 1:6, socname = c("Nama Hottentot", "Kung Bushmen",
"Thonga", "Lozi", "Mbundu", "Suku"), focus = c("GeiKhauan tribe",
"Nyai Nyae region", "Ronga subtribe", "Ruling Luyana", "Bailundo subtribe",
"Feshi territory lineage center"), hraf = c("FX13", "FX10", "FT06",
"FQ09", "FP13", NA), v1 = c(4L, 2L, 4L, 4L, NA, 4L), v3 = c(1L,
1L, 6L, 5L, 6L, 6L), v4 = c(6L, 6L, 5L, 5L, 5L, 4L), v5 = c(5L,
1L, 3L, 4L, 4L, 3L), v6 = c(7L, 8L, 3L, 7L, 7L, 1L), v7 = c(1L,
1L, 2L, 3L, 2L, 2L), v8 = c(NA, NA, 2L, 2L, 2L, 2L), v9 = c(4L,
4L, 3L, 3L, 3L, 3L), v10 = c(3L, 3L, 3L, 4L, 2L, 4L), v11 = c(3L,
5L, 2L, 2L, 2L, 3L), v12 = c(1L, 6L, 5L, 5L, 1L, 6L), v13 = c(2L,
1L, 1L, 1L, 1L, 1L), v15 = c(2L, 2L, 4L, 4L, 4L, 1L), v19 = c(1L,
1L, 7L, 12L, 7L, 2L), v20 = c(1L, 1L, 2L, 2L, 2L, 2L), v21 = c(1L,
1L, 1L, 3L, 1L, 2L), v22 = c(1L, 1L, 3L, 4L, 3L, 1L), v34 = c(4L,
4L, 5L, NA, NA, 6L), v35 = c(2L, 2L, 4L, 2L, 2L, 3L), v36 = c(3L,
1L, 4L, 4L, 3L, 3L), v61 = c(1L, 1L, 5L, 3L, 6L, 5L), v62 = c(4L,
4L, 4L, 4L, 4L, 4L), v63 = c(3L, 1L, 1L, 5L, 3L, 2L), v64 = c(1L,
1L, 6L, 4L, 4L, 4L), v65 = c(3L, 3L, 6L, 6L, 6L, 7L), v66 = c(1L,
1L, 1L, 2L, 3L, 1L), v67 = c(3L, 3L, 8L, 8L, 6L, 8L), v68 = c(2L,
8L, 12L, 3L, 3L, 9L), v72 = c(5L, 4L, 5L, 3L, 5L, 4L), v75 = c(4L,
3L, 4L, 4L, 3L, 3L), v93 = c(1L, 1L, 5L, 6L, 8L, 5L), v94 = c(0L,
0L, 10L, 3L, 3L, 0L), v95 = c(0L, 0L, 0L, 2L, 0L, 0L), v96 = c(0L,
0L, 0L, 0L, 0L, 0L), v97 = c(0L, 0L, 0L, 0L, 0L, 0L), v98 = c(0L,
0L, 0L, 0L, 0L, 0L), v144 = c(-1L, 1L, 1L, -1L, NA, 1L), v150 = c(1L,
1L, 4L, 3L, 5L, 4L), v151 = c(1L, 1L, 4L, 5L, 4L, 4L), v152 = c(2L,
1L, 1L, 4L, 2L, 1L), v153 = c(4L, 1L, 4L, 3L, 4L, 4L), v154 = c(2L,
1L, 1L, 1L, 1L, 1L), v155 = c(1L, 1L, 3L, 1L, 4L, 4L), v181 = c(18L,
22L, 33L, 23L, 15L, NA), v182 = c(1L, 1L, 1L, 1L, 1L, NA), v186 = c(21L,
21L, 24L, 23L, 18L, NA), v187 = c(27L, 25L, 27L, 25L, 19L, NA
), v188 = c(13L, 15L, 19L, 18L, 17L, NA), v189 = c(133L, 470L,
570L, 954L, 1354L, NA), v192 = c(34L, 95L, 129L, 210L, 235L,
NA), v193 = c(0L, 0L, 17L, 0L, 0L, NA), v194 = c(9L, 7L, 7L,
7L, 5L, NA), v195 = c(1L, 1L, 2L, 12L, 1L, NA), v196 = c(12L,
7L, 7L, 6L, 4L, NA), v197 = c(7L, 6L, 7L, 4L, 2L, NA), v198 = c(1L,
1L, 1L, 12L, 12L, NA), v199 = c(0L, 0L, 0L, 0L, 0L, NA), v200 = c(1L,
1L, 1L, 1L, 1L, 1L), v201 = c(1L, 1L, 2L, 2L, 2L, 3L), v203 = c(1L,
8L, 0L, 1L, 1L, 1L), v204 = c(3L, 2L, 1L, 2L, 1L, 2L), v205 = c(1L,
0L, 1L, 1L, 1L, 1L), v206 = c(5L, 0L, 3L, 2L, 2L, 0L), v207 = c(0L,
0L, 5L, 4L, 5L, 6L), v232 = c(1L, 1L, 3L, 5L, 3L, 3L), v233 = c(1L,
1L, 6L, 6L, 6L, 5L), v234 = c(1L, 1L, 7L, 3L, 7L, 7L), v236 = c(2L,
3L, 2L, 2L, 3L, 3L), v237 = c(2L, 1L, 3L, 4L, 3L, 4L), v241 = c(0L,
0L, 5L, 0L, 0L, 5L), v242 = c(2L, 2L, 3L, NA, 2L, 2L), v243 = c(1L,
1L, 1L, 1L, 1L, 1L), v244 = c(7L, 1L, 7L, 7L, 7L, 3L), v245 = c(2L,
1L, 2L, 2L, 1L, 1L), v246 = c(4L, 1L, 6L, 7L, 6L, 6L), v254 = c(9L,
9L, 3L, 3L, 3L, 3L), v255 = c(9L, 9L, 9L, 9L, 9L, NA), v256 = c(9L,
9L, 9L, 9L, 9L, NA), v257 = c(9L, 9L, 9L, 9L, 9L, 9L), v258 = c(9L,
9L, 9L, 9L, 9L, NA), v259 = c(9L, 9L, 9L, 9L, 9L, 9L), v260 = c(6L,
5L, 6L, 5L, 6L, NA), v261 = c(1L, 1L, 1L, 1L, 1L, 1L), v262 = c(1L,
9L, 1L, 2L, 2L, 4L), v263 = c(3L, 9L, 1L, 1L, 1L, NA), v264 = c(9L,
9L, 5L, 5L, 5L, 5L), v268 = c(9L, 9L, 9L, 9L, 9L, NA), v270 = c(2L,
1L, 4L, 4L, 4L, 4L), v271 = c(9L, 9L, 9L, 9L, 9L, 9L), v283 = c(2L,
2L, 2L, 2L, 2L, 5L), v284 = c(2L, 2L, 2L, 2L, 2L, 2L), v285 = c(NA,
NA, 2L, 2L, 2L, 3L), v286 = c(2L, 2L, 4L, 4L, 4L, 8L), v287 = c(7L,
8L, 8L, 8L, 8L, 8L), v288 = c(NA, 1L, NA, 5L, NA, NA), v289 = c(NA,
2L, NA, 2L, NA, NA), v291 = c(NA, 5L, NA, 8L, NA, NA), v292 = c(NA,
8L, NA, 8L, NA, NA), v457 = c(4L, 7L, 3L, NA, NA, NA), v458 = c(4L,
7L, 3L, NA, NA, NA), v459 = c(4L, 7L, 3L, 4L, NA, 7L), v460 = c(4L,
7L, 3L, NA, NA, NA), v533 = c(2L, 2L, 4L, 0L, 4L, 4L), v534 = c(2L,
2L, 3L, 2L, 3L, 0L), v535 = c(4L, 2L, 4L, 0L, 4L, 4L), v536 = c(4L,
3L, 4L, 3L, 4L, 0L), v537 = c(3L, 3L, 3L, 0L, 4L, 4L), v538 = c(3L,
3L, 3L, 3L, 4L, 0L), v539 = c(3L, 4L, 4L, 0L, 4L, 4L), v540 = c(3L,
3L, 4L, 3L, 3L, 0L), v541 = c(4L, 4L, 6L, 0L, 6L, 6L), v542 = c(3L,
3L, 4L, 4L, 5L, 0L), v543 = c(5L, 5L, 5L, 0L, 5L, 3L), v544 = c(5L,
4L, 5L, 4L, 2L, 0L), v545 = c(6L, 4L, 2L, 0L, 5L, 7L), v546 = c(6L,
6L, 3L, 6L, 5L, 0L), v547 = c(3L, 4L, 3L, 0L, 5L, 2L), v548 = c(2L,
2L, 3L, 4L, 5L, 0L), v549 = c(3L, 3L, 3L, 0L, 3L, 3L), v550 = c(3L,
3L, 3L, 3L, 3L, 0L), v551 = c(5L, 5L, 5L, 0L, 5L, 5L), v552 = c(5L,
5L, 2L, 5L, 5L, 0L), v553 = c(3L, 3L, 4L, 0L, 4L, 4L), v554 = c(2L,
3L, 4L, 3L, 4L, 0L), v555 = c(4L, 2L, 5L, 0L, 5L, 6L), v556 = c(4L,
2L, 4L, 4L, 3L, 0L), v557 = c(2L, 2L, 4L, 0L, 5L, 3L), v558 = c(2L,
2L, 2L, 4L, 5L, 0L), v559 = c(3L, 6L, 6L, 0L, 6L, 3L), v560 = c(3L,
3L, 3L, 3L, 6L, 0L), v561 = c(2L, 2L, 1L, NA, NA, 1L), v563 = c(2L,
2L, 2L, NA, NA, 1L), v564 = c(1L, 1L, 1L, NA, NA, NA), v565 = c(1L,
1L, 1L, NA, NA, 1L), v566 = c(1L, 1L, 1L, NA, NA, NA), v567 = c(1L,
1L, 1L, NA, NA, NA), v573 = c(1L, 1L, 2L, NA, NA, 1L), v574 = c(1L,
1L, 1L, NA, NA, 1L), v575 = c(1L, 1L, 2L, NA, NA, 1L), v576 = c(1L,
NA, NA, NA, 3L, NA), v577 = c(1L, NA, 3L, NA, 2L, NA), v578 = c(1L,
NA, 2L, NA, 3L, NA), v579 = c(1L, NA, 3L, NA, 4L, NA), v580 = c(2L,
NA, 3L, NA, NA, NA), v581 = c(2L, NA, 2L, NA, 2L, NA), v582 = c(2L,
NA, 1L, NA, 2L, NA), v584 = c(1L, NA, 1L, NA, 1L, NA), v587 = c(3L,
NA, 2L, NA, 2L, NA), v588 = c(NA, NA, 2L, NA, 2L, NA), v599 = c(7L,
NA, 7L, NA, 7L, NA), v617 = c(1L, NA, 2L, NA, 2L, NA), v622 = c(2L,
NA, 1L, NA, 1L, NA), v623 = c(4L, NA, 2L, NA, 1L, NA), v633 = c(3L,
NA, 3L, NA, 3L, NA), v635 = c(3L, NA, 2L, NA, 3L, NA), v652 = c(2L,
2L, 4L, NA, 2L, 3L), v653 = c(1L, 1L, 1L, NA, 1L, 1L), v654 = c(4L,
4L, 3L, NA, 3L, 2L), v655 = c(3L, 1L, 1L, NA, 3L, 3L), v656 = c(1L,
1L, 3L, NA, 1L, 3L), v665 = c(2L, 2L, 2L, NA, 2L, 2L), v671 = c(6L,
5L, 6L, NA, 3L, 5L), v672 = c(3L, 3L, 3L, 1L, 1L, 3L), v676 = c(3L,
3L, 2L, 3L, 3L, NA), v678 = c(2L, 1L, 3L, 2L, 2L, 2L), v679 = c(2L,
1L, 2L, 2L, 2L, 1L), v681 = c(1L, NA, 1L, NA, 2L, NA), v693 = c(2L,
NA, 1L, NA, 2L, NA), v694 = c(5L, NA, 3L, NA, 1L, NA), v695 = c(1L,
NA, 2L, NA, 4L, NA), v708 = c(1L, NA, 1L, NA, 1L, NA), v731 = c(3L,
NA, 4L, NA, 4L, NA), v757 = c(NA, 1L, NA, 2L, NA, 2L), v767 = c(NA,
3L, NA, 2L, NA, 3L), v768 = c(NA, 4L, NA, 3L, NA, 2L), v773 = c(NA,
3L, NA, 3L, NA, 2L), v774 = c(NA, 4L, NA, 2L, NA, 3L), v788 = c(NA,
2L, NA, 2L, NA, 2L), v790 = c(NA, 3L, NA, 1L, NA, 3L), v791 = c(NA,
1L, NA, 1L, NA, 1L), v792 = c(NA, 1L, NA, 2L, NA, 3L), v814 = c(0L,
0L, 75L, 35L, 60L, 55L), v815 = c(35L, 0L, 5L, 25L, 25L, 5L),
v816 = c(0L, 0L, 5L, 25L, 5L, 5L), v817 = c(30L, 25L, 5L,
5L, 5L, 5L), v818 = c(30L, 75L, 5L, 5L, 5L, 25L), v819 = c(5L,
0L, 5L, 5L, 0L, 5L), v820 = c(2L, 1L, 6L, 7L, 6L, 6L), v821 = c(NA,
NA, 85L, 60L, 65L, 80L), v822 = c(50L, NA, 0L, 0L, 6L, NA
), v823 = c(NA, NA, 5L, 19L, 0L, 25L), v824 = c(0L, 0L, 0L,
0L, 0L, 0L), v825 = c(25L, 25L, 75L, 56L, 57L, NA), v826 = c(26L,
19L, 71L, 30L, 43L, 70L), v833 = c(4L, 7L, 3L, 1L, 3L, 3L
), v835 = c(2L, 1L, 3L, 4L, 3L, 4L), v840 = c("FX13", "FX10",
"FT06", "FQ09e", "FP13e", NA), v843 = c("A01a", "A02a", "A03a",
"A03f", "A04a", "A05a"), v854 = c(1L, 1L, 1L, 1L, 1L, 1L),
v855 = c(7L, 7L, 2L, 2L, 2L, 2L), v856 = c(1L, 1L, 1L, 1L,
1L, 1L), v858 = c(6L, 1L, 8L, 11L, 8L, 8L), v859 = c(11L,
2L, 10L, 8L, 10L, 10L), v869 = c(0L, 0L, 0L, 0L, 0L, 0L),
v879 = c(0L, 1L, NA, NA, 0L, NA), v880 = c(1L, 0L, NA, NA,
0L, NA), v881 = c(0L, 0L, NA, NA, 1L, NA), v882 = c(0L, 0L,
NA, NA, 0L, NA), v884 = c(0L, 0L, NA, NA, 1L, NA), v898 = c(1L,
NA, NA, NA, NA, NA), v913 = c(2L, 2L, 2L, 2L, 1L, NA), v915 = c(1L,
1L, 1L, 1L, 2L, NA), v921 = c(12L, 20L, 16L, 21L, 19L, 18L
), v922 = c(4L, 8L, 8L, 8L, 7L, 8L), v924 = c(5L, 4L, 4L,
6L, 4L, 2L), v926 = c(3L, 8L, 4L, 7L, 8L, 8L), v928 = c(3L,
4L, 4L, 6L, 4L, 2L), v929 = c(1L, 5L, 3L, 7L, 8L, 8L), v930 = c(0L,
0L, 0L, 0L, 0L, 0L), v931 = c(NA, NA, 8L, NA, NA, 8L), v932 = c(NA,
NA, 1L, NA, NA, 2L), v966 = c(0L, NA, 1L, NA, NA, 6L), v1007 = c(3L,
3L, NA, NA, NA, NA), v1008 = c(0L, 0L, NA, NA, NA, NA), v1011 = c(1L,
1L, NA, NA, NA, NA), v1012 = c(2L, 1L, NA, NA, NA, NA), v1013 = c(2L,
1L, NA, NA, NA, NA), v1014 = c(2L, 2L, NA, NA, NA, NA), v1015 = c(1L,
0L, NA, NA, NA, NA), v1016 = c(0L, 0L, NA, NA, NA, NA), v1017 = c(0L,
2L, NA, NA, NA, NA), v1018 = c(1L, 0L, NA, NA, NA, NA), v1019 = c(4L,
3L, NA, NA, NA, NA), v1020 = c(3L, 3L, NA, NA, NA, NA), v1021 = c(1L,
2L, NA, NA, NA, NA), v1022 = c(0L, 0L, NA, NA, NA, NA), v1023 = c(0L,
0L, NA, NA, NA, NA), v1026 = c(0L, 0L, NA, NA, NA, NA), v1027 = c(1L,
0L, NA, NA, NA, NA), v1028 = c(0L, 0L, NA, NA, NA, NA), v1029 = c(0L,
0L, NA, NA, NA, NA), v1030 = c(0L, 0L, NA, NA, NA, NA), v1032 = c(1L,
1L, NA, NA, NA, NA), v1033 = c(0L, 0L, NA, NA, NA, NA), v1034 = c(0L,
0L, NA, NA, NA, NA), v1035 = c(0L, 0L, NA, NA, NA, NA), v1036 = c(1L,
0L, NA, NA, NA, NA), v1037 = c(1L, 1L, NA, NA, NA, NA), v1038 = c(1L,
1L, NA, NA, NA, NA), v1047 = c(1L, 0L, NA, NA, NA, NA), v1048 = c(1L,
0L, NA, NA, NA, NA), v1049 = c(0L, 1L, NA, NA, NA, NA), v1050 = c(0L,
0L, NA, NA, NA, NA), v1054 = c(0L, 0L, NA, NA, NA, NA), v1055 = c(1L,
0L, NA, NA, NA, NA), v1056 = c(0L, 0L, NA, NA, NA, NA), v1059 = c(0L,
0L, NA, NA, NA, NA), v1123 = c(0L, 0L, 14L, 15L, 14L, 24L
), v1125 = c(0L, 0L, 1L, 1L, 1L, 1L), v1127 = c(0L, 0L, 1L,
1L, 1L, 1L), v1128 = c(0L, 0L, 1L, 4L, 4L, 1L), v1132 = c(4L,
2L, 5L, 6L, 2L, 0L), v1188 = c(3L, 3L, 7L, 3L, 2L, 3L), v1189 = c(0L,
0L, 1L, 0L, 0L, 0L), v1253 = c(1L, 1L, 1L, 1L, 1L, 2L), v1254 = c(1L,
2L, 1L, 2L, 2L, 2L), v1255 = c(1L, 3L, 3L, 3L, 3L, 3L), v1256 = c(1L,
1L, 2L, 2L, 1L, 2L), v1257 = c(1L, 1L, 1L, 3L, 3L, 3L), v1258 = c(1L,
1L, 1L, 2L, 3L, 3L), v1259 = c(2L, 1L, 2L, 3L, 2L, 3L), v1260 = c(8L,
10L, 11L, 16L, 15L, 18L), v1262 = c(2L, 3L, 2L, 2L, 2L, NA
), v1263 = c(3L, 4L, 3L, 1L, 3L, NA), v1352 = c(0L, 0L, 1L,
NA, NA, 0L), v1354 = c(0L, 0L, NA, NA, NA, 0L), v1355 = c(0L,
0L, 0L, NA, NA, 0L), v1362 = c(0L, 0L, NA, NA, NA, NA), v1458 = c(0L,
0L, NA, NA, NA, NA), v1489 = c(0L, 0L, 1L, NA, NA, 2L), v1666 = c(NA,
1L, NA, NA, NA, 7L), v1683 = c(NA, 3L, 4L, NA, 1L, NA), v1684 = c(2L,
4L, NA, NA, 1L, NA), v1685 = c(3L, 4L, 4L, 1L, 1L, 1L), v1686 = c(1L,
8L, 3L, 1L, 1L, 1L), v1687 = c(1L, 5L, 8L, 1L, 8L, 1L), v1688 = c(8L,
1L, 8L, 4L, 8L, 8L), v1692 = c(2L, 2L, 2L, 1L, 2L, 1L), v1693 = c(1L,
2L, 1L, 2L, NA, 1L), v1694 = c(3L, 3L, 2L, 1L, 3L, 1L), v1695 = c(2L,
3L, 3L, 3L, NA, 1L), v1697 = c(1L, 1L, 1L, 1L, 2L, 3L), v1698 = c(1L,
1L, 1L, 1L, 1L, 1L), v1699 = c(1L, 1L, 1L, 1L, 1L, 1L), v1700 = c(1L,
1L, 1L, 1L, 1L, 3L), v1701 = c(1L, 1L, 2L, 1L, 2L, 2L), v1702 = c(1L,
1L, 1L, 1L, 1L, 1L), v1703 = c(1L, 1L, 1L, 1L, 1L, 2L), v1704 = c(1L,
1L, 1L, 1L, 1L, 3L), v1705 = c(1L, 1L, 3L, 3L, 3L, 1L), v1706 = c(1L,
1L, 1L, 3L, 2L, 1L), v1707 = c(1L, 2L, 3L, 3L, 3L, 3L), v1708 = c(1L,
1L, 2L, 3L, 1L, 1L), v1709 = c(1L, 1L, 1L, 3L, 3L, 1L), v1745 = c(NA,
0L, 3L, 3L, NA, 1L), v1767 = c(NA, 2L, 1L, NA, NA, NA), v1779 = c(NA,
NA, 3L, 1L, NA, 1L), v1780 = c(NA, NA, 3L, 3L, NA, NA), v1850 = c(1L,
1L, 1L, 1L, 1L, NA), v1851 = c(1L, 7L, 1L, 1L, 1L, NA), v1852 = c(1L,
1L, 1L, 1L, 1L, NA), v1853 = c(1L, 2L, 1L, 1L, 1L, NA), v1854 = c(1L,
1L, 1L, 1L, 1L, NA), v1855 = c(1L, 2L, 1L, 1L, 1L, NA), v1856 = c(1L,
1L, 1L, 1L, 1L, NA), v1857 = c(1L, 1L, 1L, 1L, 1L, NA), v1858 = c(1L,
1L, 1L, 1L, 1L, 1L), v1889 = c(0L, 0L, 1L, 0L, 0L, 0L), v1890 = c(0L,
0L, 0L, 0L, 0L, 0L), v1892 = c(1L, 0L, 1L, 0L, 0L, 0L), v1893 = c(0L,
0L, 0L, 0L, 0L, 0L), v1895 = c(1L, 0L, 1L, 0L, 1L, 0L), v1896 = c(0L,
0L, 0L, 0L, 0L, 0L), v1898 = c(1L, 0L, 1L, 0L, 1L, 0L), v1899 = c(0L,
0L, 0L, 0L, 0L, 1L), v1900 = c(2L, 2L, 2L, 2L, 2L, 2L), v1901 = c(2L,
2L, 2L, 2L, 2L, 2L), v1902 = c(2L, 2L, 2L, 2L, 2L, 2L), v1903 = c(2L,
2L, 2L, 2L, 2L, 2L), v1913 = c(11.155, 35.425, 86.95, 69.79,
128.05, 165.89), v2001 = c(1L, 1L, 1L, 1L, 1L, 1L), v2002 = c(1L,
1L, 1L, 1L, 1L, 1L), v2003 = c(3L, 2L, 2L, 2L, 1L, 1L), v2004 = c(3L,
3L, 3L, 3L, 3L, 3L), v2005 = c(2L, 2L, 2L, 2L, 1L, 1L), v2006 = c(2L,
1L, 2L, 2L, 2L, 1L), v2007 = c(1L, 3L, 3L, 2L, 2L, 2L), v2013 = c(1L,
1L, 2L, 2L, 2L, 2L), v2039 = c(NA, 1L, NA, NA, NA, NA), v2106 = c(NA_integer_,
NA_integer_, NA_integer_, NA_integer_, NA_integer_, NA_integer_
), v2126 = c(1L, 1L, 1L, 1L, 1L, 1L), v2127 = c(1L, 1L, 1L,
1L, 1L, 1L), v2128 = c(1L, 0L, 1L, 0L, 0L, 0L), v2129 = c(1L,
1L, 1L, 1L, 1L, 1L), v2130 = c(1L, 1L, 1L, 1L, 1L, 1L), v2131 = c(1L,
0L, 1L, 1L, 1L, 1L), v2132 = c(1L, 1L, 1L, 1L, 1L, 1L), v2133 = c(1L,
1L, 1L, 1L, 1L, 1L), v2134 = c(1L, 0L, 1L, 1L, 0L, 0L), v2135 = c(0L,
0L, 1L, 1L, 1L, 1L), v2136 = c(0L, 0L, 1L, 1L, 1L, 1L), v2137 = c(0L,
0L, 1L, 1L, 1L, 1L), v2138 = c(0L, 0L, 1L, 1L, 1L, 1L), v2139 = c(0L,
0L, 1L, 1L, 1L, 1L), v2140 = c(1L, 1L, 1L, NA, 1L, 1L), v2141 = c(1L,
0L, 1L, 1L, 1L, 0L), v2142 = c(1L, 0L, 1L, 1L, 0L, 0L), v2143 = c(1L,
1L, 1L, 1L, 1L, 1L), v2144 = c(1L, 1L, 1L, 1L, 1L, 1L), v2145 = c(1L,
1L, NA, 1L, NA, 0L), v2146 = c(1L, 0L, 1L, NA, 1L, 1L), v2147 = c(1L,
0L, 1L, NA, 0L, 0L), v2148 = c(1L, 1L, 1L, 1L, 1L, 1L), v2149 = c(NA,
0L, 0L, 0L, 1L, NA), v2150 = c(1L, 1L, 1L, 1L, 1L, 1L), v2151 = c(NA,
0L, 1L, 1L, 1L, 1L), v2152 = c(1L, 1L, 1L, 1L, 1L, 1L), v2153 = c(1L,
1L, 0L, 1L, 1L, 1L), v2154 = c(0L, 0L, NA, 0L, 1L, NA), v2155 = c(0L,
0L, NA, 1L, NA, 1L), v2156 = c(1L, 0L, 1L, 0L, 1L, 0L), v2157 = c(1L,
0L, 1L, 1L, 1L, 1L), v2158 = c(1L, 0L, 0L, 1L, 1L, 1L), v2159 = c(1L,
0L, 1L, 1L, 1L, 1L), v2160 = c(1L, 1L, 1L, 1L, 1L, 1L), v2161 = c(1L,
1L, 0L, 1L, 1L, NA), v2162 = c(1L, 1L, 1L, 1L, 0L, 0L), v2163 = c(1L,
0L, 1L, 1L, 1L, 1L), v2164 = c(1L, 1L, 1L, 1L, 1L, 1L), v2165 = c(1L,
1L, 1L, 1L, 0L, NA), v2166 = c(1L, 0L, 0L, 0L, 0L, 0L), v2167 = c(1L,
0L, 1L, 0L, 1L, 1L), v2169 = c(1L, 1L, 1L, 1L, 1L, 1L), v2171 = c(1L,
1L, 1L, 1L, NA, 1L), v2173 = c(1L, 1L, 1L, 1L, 1L, NA), v2174 = c(0L,
0L, 1L, 1L, 1L, 0L), v2175 = c(1L, 1L, 1L, 1L, 1L, 1L), v2177 = c(13L,
14L, 17L, 18L, 18L, 21L), v2178 = c(-0.42, -0.4, 0.1, 0.46,
0.31, 0.69), v2180 = c(NA, NA, 0L, NA, NA, NA), v2181 = c(NA,
NA, 0L, NA, 2L, NA), bio.1 = c(196, 215, 226, 229, 197, 225
), bio.10 = c(243, 251, 256, 256, 210, 232), bio.11 = c(138,
158, 190, 191, 174, 214), bio.12 = c(279, 454, 790, 971,
1283, 1681), bio.13 = c(70, 126, 160, 218, 241, 231), bio.14 = c(0,
0, 16, 0, 0, 12), bio.15 = c(107, 109, 68, 106, 84, 56),
bio.16 = c(196, 298, 386, 620, 625, 658), bio.17 = c(1, 0,
54, 0, 2, 75), bio.18 = c(150, 142, 386, 143, 337, 579),
bio.19 = c(1, 0, 54, 5, 18, 75), bio.2 = c(170, 158, 104,
149, 128, 115), bio.3 = c(58, 56, 57, 56, 62, 77), bio.4 = c(4166,
3903, 2560, 2600, 1439, 708), bio.5 = c(329, 335, 306, 354,
290, 287), bio.6 = c(37, 55, 125, 92, 85, 139), bio.7 = c(292,
280, 181, 262, 205, 148), bio.8 = c(235, 249, 256, 240, 203,
226), bio.9 = c(138, 158, 190, 192, 177, 214), continent = c("Africa",
"Africa", "Africa", "Africa", "Africa", "Africa"), ecoregion = c("Kalahari Xeric Savanna",
"Kalahari Acacia-Baikiaea Woodland", "Maputaland Coastal Forest",
"Zambezian Flooded Grassland", "Angolan Miombo Woodland",
"Southern Congolian Forest-Savanna Mosaic"), koeppengei = c("BWh",
"BSh", "Aw", "Aw", "BSh", "Aw"), lati = c(-23.31667, -19.8,
-25.966667, -15.19374, -12.2, -6.125174), long = c(17.08333,
20.56667, 32.583333, 23.00351, 15.86667, 18.15378), meanalt = c(1430.615,
1160.31510416667, 24.7480916030534, 1015.40633245383, 1501.58333333333,
847.565573770492), mht.name = c("Deserts and xeric shrublands",
"Tropical and subtropical grasslands, savannas, and shrublands",
"Tropical and subtropical moist broadleaf forests", "Flooded grasslands",
"Tropical and subtropical grasslands, savannas, and shrublands",
"Tropical and subtropical grasslands, savannas, and shrublands"
), mnnpp = c(-1.08114663311421, -0.73944547744944, -1.11362452325029,
0.140172087096408, 0.74204476271665, 0.583531521680504),
region = c("Southern Africa", "Southern Africa", "Eastern Africa",
"Eastern Africa", "Middle Africa", "Middle Africa"), religious_edifice = c("Absent",
"Absent", "Absent", "Absent", "Absent", "Absent")), .Names = c("V1_A",
"ord", "socname", "focus", "hraf", "v1", "v3", "v4", "v5", "v6",
"v7", "v8", "v9", "v10", "v11", "v12", "v13", "v15", "v19", "v20",
"v21", "v22", "v34", "v35", "v36", "v61", "v62", "v63", "v64",
"v65", "v66", "v67", "v68", "v72", "v75", "v93", "v94", "v95",
"v96", "v97", "v98", "v144", "v150", "v151", "v152", "v153",
"v154", "v155", "v181", "v182", "v186", "v187", "v188", "v189",
"v192", "v193", "v194", "v195", "v196", "v197", "v198", "v199",
"v200", "v201", "v203", "v204", "v205", "v206", "v207", "v232",
"v233", "v234", "v236", "v237", "v241", "v242", "v243", "v244",
"v245", "v246", "v254", "v255", "v256", "v257", "v258", "v259",
"v260", "v261", "v262", "v263", "v264", "v268", "v270", "v271",
"v283", "v284", "v285", "v286", "v287", "v288", "v289", "v291",
"v292", "v457", "v458", "v459", "v460", "v533", "v534", "v535",
"v536", "v537", "v538", "v539", "v540", "v541", "v542", "v543",
"v544", "v545", "v546", "v547", "v548", "v549", "v550", "v551",
"v552", "v553", "v554", "v555", "v556", "v557", "v558", "v559",
"v560", "v561", "v563", "v564", "v565", "v566", "v567", "v573",
"v574", "v575", "v576", "v577", "v578", "v579", "v580", "v581",
"v582", "v584", "v587", "v588", "v599", "v617", "v622", "v623",
"v633", "v635", "v652", "v653", "v654", "v655", "v656", "v665",
"v671", "v672", "v676", "v678", "v679", "v681", "v693", "v694",
"v695", "v708", "v731", "v757", "v767", "v768", "v773", "v774",
"v788", "v790", "v791", "v792", "v814", "v815", "v816", "v817",
"v818", "v819", "v820", "v821", "v822", "v823", "v824", "v825",
"v826", "v833", "v835", "v840", "v843", "v854", "v855", "v856",
"v858", "v859", "v869", "v879", "v880", "v881", "v882", "v884",
"v898", "v913", "v915", "v921", "v922", "v924", "v926", "v928",
"v929", "v930", "v931", "v932", "v966", "v1007", "v1008", "v1011",
"v1012", "v1013", "v1014", "v1015", "v1016", "v1017", "v1018",
"v1019", "v1020", "v1021", "v1022", "v1023", "v1026", "v1027",
"v1028", "v1029", "v1030", "v1032", "v1033", "v1034", "v1035",
"v1036", "v1037", "v1038", "v1047", "v1048", "v1049", "v1050",
"v1054", "v1055", "v1056", "v1059", "v1123", "v1125", "v1127",
"v1128", "v1132", "v1188", "v1189", "v1253", "v1254", "v1255",
"v1256", "v1257", "v1258", "v1259", "v1260", "v1262", "v1263",
"v1352", "v1354", "v1355", "v1362", "v1458", "v1489", "v1666",
"v1683", "v1684", "v1685", "v1686", "v1687", "v1688", "v1692",
"v1693", "v1694", "v1695", "v1697", "v1698", "v1699", "v1700",
"v1701", "v1702", "v1703", "v1704", "v1705", "v1706", "v1707",
"v1708", "v1709", "v1745", "v1767", "v1779", "v1780", "v1850",
"v1851", "v1852", "v1853", "v1854", "v1855", "v1856", "v1857",
"v1858", "v1889", "v1890", "v1892", "v1893", "v1895", "v1896",
"v1898", "v1899", "v1900", "v1901", "v1902", "v1903", "v1913",
"v2001", "v2002", "v2003", "v2004", "v2005", "v2006", "v2007",
"v2013", "v2039", "v2106", "v2126", "v2127", "v2128", "v2129",
"v2130", "v2131", "v2132", "v2133", "v2134", "v2135", "v2136",
"v2137", "v2138", "v2139", "v2140", "v2141", "v2142", "v2143",
"v2144", "v2145", "v2146", "v2147", "v2148", "v2149", "v2150",
"v2151", "v2152", "v2153", "v2154", "v2155", "v2156", "v2157",
"v2158", "v2159", "v2160", "v2161", "v2162", "v2163", "v2164",
"v2165", "v2166", "v2167", "v2169", "v2171", "v2173", "v2174",
"v2175", "v2177", "v2178", "v2180", "v2181", "bio.1", "bio.10",
"bio.11", "bio.12", "bio.13", "bio.14", "bio.15", "bio.16", "bio.17",
"bio.18", "bio.19", "bio.2", "bio.3", "bio.4", "bio.5", "bio.6",
"bio.7", "bio.8", "bio.9", "continent", "ecoregion", "koeppengei",
"lati", "long", "meanalt", "mht.name", "mnnpp", "region", "religious_edifice"
), row.names = c(NA, -6L), class = c("tbl_df", "tbl", "data.frame"
))
以下是代码：
library(lattice)
library(mice)
init = mice(SCCS4, maxit=0)
meth = init$method
predM = init$predictorMatrix
predM[, c("V1_A")]=0
predM[, c("ord")]=0
predM[, c("socname")]=0
predM[, c("focus")]=0
predM[, c("hraf")]=0
meth[c("continent")]=""
meth[c("ecoregion")]=""
meth[c("koeppengei")]=""
meth[c("lati")]=""
meth[c("long")]=""
meth[c("meanalt")]=""
meth[c("mht.name")]=""
meth[c("mnnpp")]=""
meth[c("region")]=""
meth[c("v285")]=""
meth[c("v288")]=""
meth[c("v289")]=""
meth[c("v291")]=""
meth[c("v292")]=""
meth[c("v582")]=""
meth[c("v587")]=""
meth[c("v588")]=""
meth[c("v617")]=""
meth[c("v695")]=""
meth[c("v708")]=""
meth[c("v788")]=""
meth[c("v840")]=""
meth[c("v843")]=""
meth[c("v1007")]=""
meth[c("v1008")]=""
meth[c("v1011")]=""
meth[c("v1012")]=""
meth[c("v1013")]=""
meth[c("v1014")]=""
meth[c("v1015")]=""
meth[c("v1016")]=""
meth[c("v1017")]=""
meth[c("v1018")]=""
meth[c("v1019")]=""
meth[c("v1020")]=""
meth[c("v1021")]=""
meth[c("v1022")]=""
meth[c("v1023")]=""
meth[c("v1026")]=""
meth[c("v1027")]=""
meth[c("v1028")]=""
meth[c("v1029")]=""
meth[c("v1030")]=""
meth[c("v1032")]=""
meth[c("v1033")]=""
meth[c("v1034")]=""
meth[c("v1035")]=""
meth[c("v1036")]=""
meth[c("v1037")]=""
meth[c("v1038")]=""
meth[c("v1047")]=""
meth[c("v1048")]=""
meth[c("v1049")]=""
meth[c("v1050")]=""
meth[c("v1054")]=""
meth[c("v1055")]=""
meth[c("v1056")]=""
meth[c("v1059")]=""
meth[c("v1352")]=""
meth[c("v1354")]=""
meth[c("v1355")]=""
meth[c("v1362")]=""
meth[c("v1458")]=""
meth[c("v1489")]=""
meth[c("v1779")]=""
meth[c("v1780")]=""
meth[c("v2129")]=""
imputed = mice(SCCS4, method=meth, predictorMatrix=predM, m=5)
iter imp variable
1 1 v1Error in cor(xobs[, keep, drop = FALSE], use = "all.obs") : 'x' is empty
@qdread - 我相信这是源代码（使用getAnywhere（mice））。
function (data, m = 5, method = vector("character", length = ncol(data)),
predictorMatrix = (1 - diag(1, ncol(data))), where = is.na(data),
visitSequence = NULL, form = vector("character", length = ncol(data)),
post = vector("character", length = ncol(data)), defaultMethod = c("pmm",
"logreg", "polyreg", "polr"), maxit = 5, diagnostics = TRUE,
printFlag = TRUE, seed = NA, imputationMethod = NULL, defaultImputationMethod = NULL,
data.init = NULL, ...)
{
call <- match.call()
if (!is.na(seed))
set.seed(seed)
if (!(is.matrix(data) || is.data.frame(data)))
stop("Data should be a matrix or data frame")
nvar <- ncol(data)
if (nvar < 2)
stop("Data should contain at least two columns")
data <- as.data.frame(data)
nmis <- apply(is.na(data), 2, sum)
varnames <- colnames(data)
if (!(is.matrix(where) || is.data.frame(where)))
stop("Argument `where` not a matrix or data frame")
if (!all(dim(data) == dim(where)))
stop("Arguments `data` and `where` not of same size")
nwhere <- apply(where, 2, sum)
state <- list(it = 0, im = 0, co = 0, dep = "", meth = "",
log = FALSE)
loggedEvents <- data.frame(it = 0, im = 0, co = 0, dep = "",
meth = "", out = "")
if (!is.null(imputationMethod))
method <- imputationMethod
if (!is.null(defaultImputationMethod))
defaultMethod <- defaultImputationMethod
setup <- list(visitSequence = visitSequence, method = method,
defaultMethod = defaultMethod, predictorMatrix = predictorMatrix,
form = form, post = post, nvar = nvar, nmis = nmis, nwhere = nwhere,
varnames = varnames)
setup <- check.visitSequence(setup, where)
setup <- check.method(setup, data)
setup <- check.predictorMatrix(setup)
setup <- check.data(setup, data, ...)
method <- setup$method
predictorMatrix <- setup$predictorMatrix
visitSequence <- setup$visitSequence
post <- setup$post
p <- padModel(data, method, predictorMatrix, visitSequence,
form, post, nvar)
r <- (!is.na(p$data))
imp <- vector("list", ncol(p$data))
if (m > 0) {
for (j in visitSequence) {
y <- data[, j]
ry <- r[, j]
wy <- where[, j]
imp[[j]] <- as.data.frame(matrix(NA, nrow = sum(wy),
ncol = m))
dimnames(imp[[j]]) <- list(row.names(data)[wy], 1:m)
if (method[j] != "") {
for (i in seq_len(m)) {
if (nmis[j] < nrow(data)) {
if (is.null(data.init)) {
imp[[j]][, i] <- mice.impute.sample(y,
ry, wy = wy, ...)
}
else {
imp[[j]][, i] <- data.init[wy, j]
}
}
else imp[[j]][, i] <- rnorm(nrow(data))
}
}
}
}
from <- 1
to <- from + maxit - 1
q <- sampler(p, data, where, m, imp, r, visitSequence, c(from,
to), printFlag, ...)
for (j in p$visitSequence) {
p$data[!r[, j], j] <- NA
}
imp <- q$imp[seq_len(nvar)]
names(imp) <- varnames
names(method) <- varnames
names(form) <- varnames
names(post) <- varnames
names(visitSequence) <- varnames[visitSequence]
if (!state$log)
loggedEvents <- NULL
if (state$log)
row.names(loggedEvents) <- seq_len(nrow(loggedEvents))
midsobj <- list(call = call, data = as.data.frame(p$data[,
seq_len(nvar)]), where = where, m = m, nmis = nmis, imp = imp,
method = method, predictorMatrix = predictorMatrix, visitSequence = visitSequence,
form = form, post = post, seed = seed, iteration = q$iteration,
lastSeedValue = .Random.seed, chainMean = q$chainMean,
chainVar = q$chainVar, loggedEvents = loggedEvents, pad = p)
if (!diagnostics)
midsobj$pad <- NULL
oldClass(midsobj) <- "mids"
return(midsobj)
}
<bytecode: 0x10e254e00>
<environment: namespace:mice>
>