我正在将lmeSplines 教程的代码翻译成 RPy。
我现在被困在以下行:
fit1s <- lme(y ~ time, data=smSplineEx1,random=list(all=pdIdent(~Zt - 1)))
我以前工作nlme.lme
过,以下工作很好:
from rpy2.robjects.packages import importr
nlme = importr('nlme')
nlme.lme(r.formula('y ~ time'), data=some_data, random=r.formula('~1|ID'))
但这有另一个random
任务。我想知道如何翻译这一位并将其也放入我的 RPy 代码中list(all=pdIdent(~Zt - 1))
。
(预处理的)示例数据的结构smSplineEx1
如下所示(Zt.* 高达 98):
time y y.true all Zt.1 Zt.2 Zt.3
1 1 5.797149 4.235263 1 1.168560e+00 2.071261e+00 2.944953e+00
2 2 5.469222 4.461302 1 1.487859e-01 1.072013e+00 1.948857e+00
3 3 4.567237 4.678477 1 -5.449190e-02 7.276623e-02 9.527613e-01
4 4 3.645763 4.887137 1 -5.364552e-02 -1.359115e-01 -4.333438e-02
5 5 5.094126 5.087615 1 -5.279913e-02 -1.337708e-01 -2.506194e-01
6 6 4.636121 5.280233 1 -5.195275e-02 -1.316300e-01 -2.466158e-01
7 7 5.501538 5.465298 1 -5.110637e-02 -1.294892e-01 -2.426123e-01
8 8 5.011509 5.643106 1 -5.025998e-02 -1.273485e-01 -2.386087e-01
9 9 6.114037 5.813942 1 -4.941360e-02 -1.252077e-01 -2.346052e-01
10 10 5.696472 5.978080 1 -4.856722e-02 -1.230670e-01 -2.306016e-01
11 11 6.615363 6.135781 1 -4.772083e-02 -1.209262e-01 -2.265980e-01
12 12 8.002526 6.287300 1 -4.687445e-02 -1.187854e-01 -2.225945e-01
13 13 6.887444 6.432877 1 -4.602807e-02 -1.166447e-01 -2.185909e-01
14 14 6.319205 6.572746 1 -4.518168e-02 -1.145039e-01 -2.145874e-01
15 15 6.482771 6.707130 1 -4.433530e-02 -1.123632e-01 -2.105838e-01
16 16 7.938015 6.836245 1 -4.348892e-02 -1.102224e-01 -2.065802e-01
17 17 7.585533 6.960298 1 -4.264253e-02 -1.080816e-01 -2.025767e-01
18 18 7.560287 7.079486 1 -4.179615e-02 -1.059409e-01 -1.985731e-01
19 19 7.571020 7.194001 1 -4.094977e-02 -1.038001e-01 -1.945696e-01
20 20 8.922418 7.304026 1 -4.010338e-02 -1.016594e-01 -1.905660e-01
21 21 8.241394 7.409737 1 -3.925700e-02 -9.951861e-02 -1.865625e-01
22 22 7.447076 7.511303 1 -3.841062e-02 -9.737785e-02 -1.825589e-01
23 23 7.317292 7.608886 1 -3.756423e-02 -9.523709e-02 -1.785553e-01
24 24 7.077333 7.702643 1 -3.671785e-02 -9.309633e-02 -1.745518e-01
25 25 8.268601 7.792723 1 -3.587147e-02 -9.095557e-02 -1.705482e-01
26 26 8.216013 7.879272 1 -3.502508e-02 -8.881481e-02 -1.665447e-01
27 27 8.968495 7.962427 1 -3.417870e-02 -8.667405e-02 -1.625411e-01
28 28 9.085605 8.042321 1 -3.333232e-02 -8.453329e-02 -1.585375e-01
29 29 9.002575 8.119083 1 -3.248593e-02 -8.239253e-02 -1.545340e-01
30 30 8.763187 8.192835 1 -3.163955e-02 -8.025177e-02 -1.505304e-01
31 31 8.936370 8.263695 1 -3.079317e-02 -7.811101e-02 -1.465269e-01
32 32 9.033403 8.331776 1 -2.994678e-02 -7.597025e-02 -1.425233e-01
33 33 8.248328 8.397188 1 -2.910040e-02 -7.382949e-02 -1.385198e-01
34 34 5.961721 8.460035 1 -2.825402e-02 -7.168873e-02 -1.345162e-01
35 35 8.400489 8.520418 1 -2.740763e-02 -6.954797e-02 -1.305126e-01
36 36 6.855125 8.578433 1 -2.656125e-02 -6.740721e-02 -1.265091e-01
37 37 9.798931 8.634174 1 -2.571487e-02 -6.526645e-02 -1.225055e-01
38 38 8.862758 8.687729 1 -2.486848e-02 -6.312569e-02 -1.185020e-01
39 39 7.282970 8.739184 1 -2.402210e-02 -6.098493e-02 -1.144984e-01
40 40 7.484208 8.788621 1 -2.317572e-02 -5.884417e-02 -1.104949e-01
41 41 8.404670 8.836120 1 -2.232933e-02 -5.670341e-02 -1.064913e-01
42 42 8.880734 8.881756 1 -2.148295e-02 -5.456265e-02 -1.024877e-01
43 43 8.826189 8.925603 1 -2.063657e-02 -5.242189e-02 -9.848418e-02
44 44 9.827906 8.967731 1 -1.979018e-02 -5.028113e-02 -9.448062e-02
45 45 8.528795 9.008207 1 -1.894380e-02 -4.814037e-02 -9.047706e-02
46 46 9.484073 9.047095 1 -1.809742e-02 -4.599961e-02 -8.647351e-02
47 47 8.911947 9.084459 1 -1.725103e-02 -4.385885e-02 -8.246995e-02
48 48 10.201343 9.120358 1 -1.640465e-02 -4.171809e-02 -7.846639e-02
49 49 8.908016 9.154849 1 -1.555827e-02 -3.957733e-02 -7.446283e-02
50 50 8.202368 9.187988 1 -1.471188e-02 -3.743657e-02 -7.045927e-02
51 51 7.432851 9.219828 1 -1.386550e-02 -3.529581e-02 -6.645572e-02
52 52 8.063268 9.250419 1 -1.301912e-02 -3.315505e-02 -6.245216e-02
53 53 10.155756 9.279810 1 -1.217273e-02 -3.101429e-02 -5.844860e-02
54 54 7.905281 9.308049 1 -1.132635e-02 -2.887353e-02 -5.444504e-02
55 55 9.688337 9.335181 1 -1.047997e-02 -2.673277e-02 -5.044148e-02
56 56 9.437176 9.361249 1 -9.633582e-03 -2.459201e-02 -4.643793e-02
57 57 9.165873 9.386295 1 -8.787198e-03 -2.245125e-02 -4.243437e-02
58 58 9.120195 9.410358 1 -7.940815e-03 -2.031049e-02 -3.843081e-02
59 59 9.955840 9.433479 1 -7.094432e-03 -1.816973e-02 -3.442725e-02
60 60 9.314230 9.455692 1 -6.248048e-03 -1.602897e-02 -3.042369e-02
61 61 9.706852 9.477035 1 -5.401665e-03 -1.388821e-02 -2.642014e-02
62 62 9.615765 9.497541 1 -4.555282e-03 -1.174746e-02 -2.241658e-02
63 63 7.918843 9.517242 1 -3.708898e-03 -9.606695e-03 -1.841302e-02
64 64 9.352892 9.536172 1 -2.862515e-03 -7.465935e-03 -1.440946e-02
65 65 9.722685 9.554359 1 -2.016132e-03 -5.325176e-03 -1.040590e-02
66 66 9.186888 9.571832 1 -1.169748e-03 -3.184416e-03 -6.402346e-03
67 67 8.652299 9.588621 1 -3.233650e-04 -1.043656e-03 -2.398788e-03
68 68 8.681421 9.604751 1 5.230184e-04 1.097104e-03 1.604770e-03
69 69 10.279181 9.620249 1 1.369402e-03 3.237864e-03 5.608328e-03
70 70 9.314963 9.635140 1 2.215785e-03 5.378623e-03 9.611886e-03
71 71 6.897151 9.649446 1 3.062168e-03 7.519383e-03 1.361544e-02
72 72 9.343135 9.663191 1 3.908552e-03 9.660143e-03 1.761900e-02
73 73 9.273135 9.676398 1 4.754935e-03 1.180090e-02 2.162256e-02
74 74 10.041796 9.689086 1 5.601318e-03 1.394166e-02 2.562612e-02
75 75 9.724713 9.701278 1 6.447702e-03 1.608242e-02 2.962968e-02
76 76 8.593517 9.712991 1 7.294085e-03 1.822318e-02 3.363323e-02
77 77 7.401988 9.724244 1 8.140468e-03 2.036394e-02 3.763679e-02
78 78 10.258688 9.735057 1 8.986852e-03 2.250470e-02 4.164035e-02
79 79 10.037192 9.745446 1 9.833235e-03 2.464546e-02 4.564391e-02
80 80 9.637510 9.755427 1 1.067962e-02 2.678622e-02 4.964747e-02
81 81 8.887625 9.765017 1 1.152600e-02 2.892698e-02 5.365102e-02
82 82 9.922013 9.774230 1 1.237239e-02 3.106774e-02 5.765458e-02
83 83 10.466709 9.783083 1 1.321877e-02 3.320850e-02 6.165814e-02
84 84 11.132830 9.791588 1 1.406515e-02 3.534926e-02 6.566170e-02
85 85 10.154038 9.799760 1 1.491154e-02 3.749002e-02 6.966526e-02
86 86 10.433068 9.807612 1 1.575792e-02 3.963078e-02 7.366881e-02
87 87 9.666781 9.815156 1 1.660430e-02 4.177154e-02 7.767237e-02
88 88 9.478004 9.822403 1 1.745069e-02 4.391230e-02 8.167593e-02
89 89 10.002749 9.829367 1 1.829707e-02 4.605306e-02 8.567949e-02
90 90 7.593259 9.836058 1 1.914345e-02 4.819382e-02 8.968305e-02
91 91 10.915754 9.842486 1 1.998984e-02 5.033458e-02 9.368660e-02
92 92 8.855580 9.848662 1 2.083622e-02 5.247534e-02 9.769016e-02
93 93 8.884683 9.854596 1 2.168260e-02 5.461610e-02 1.016937e-01
94 94 9.757451 9.860298 1 2.252899e-02 5.675686e-02 1.056973e-01
95 95 10.222361 9.865775 1 2.337537e-02 5.889762e-02 1.097008e-01
96 96 9.090410 9.871038 1 2.422175e-02 6.103838e-02 1.137044e-01
97 97 8.837872 9.876095 1 2.506814e-02 6.317914e-02 1.177080e-01
98 98 9.413135 9.880953 1 2.591452e-02 6.531990e-02 1.217115e-01
99 99 9.295531 9.885621 1 2.676090e-02 6.746066e-02 1.257151e-01
100 100 9.698118 9.890106 1 2.760729e-02 6.960142e-02 1.297186e-01