我尝试运行以下代码:
sis.fit <- SIS(y = Surv(time = y[, 1], event = y[, 2]), x = x,
family = "cox", penalty = "lasso", tune = "cv",
nfolds = 10, type.measure = "deviance", nsis = min(dim(x)),
iter = FALSE, seed = 334)
我收到以下错误:
名称错误(coef.beta)=粘贴(&#34; X&#34;,ix1,sep =&#34;&#34;): &#39;名称&#39; attribute [1]的长度必须与vector [0]
的长度相同数据集的详细信息是:
头(y)的 #time status #1 24 1 #2 31 0 #3 39 0 #4 64 1 #5 72 1 #6 6 0 STR(y)的 #num [1:46,1:2] 24 31 39 64 72 6 87 17 53 54 ... # - attr(*,&#34; dimnames&#34;)= 2的列表 #.. $:chr [1:46]&#34; 1&#34; &#34; 2&#34; &#34; 3&#34; &#34; 4&#34; ... #.. $:chr [1:2]&#34;时间&#34; &#34;状态&#34;
>str(x)
# num [1:46, 1:66] 0.59234 0.30042 0.28278 -0.00966 0.08189 ...
# - attr(*, "dimnames")=List of 2
# ..$ : chr [1:46] "1" "2" "3" "4" ...
# ..$ : chr [1:66] "EIF4EBP1" "TP53BP1" "AKT1.AKT2.AKT3" "AR" ...
sessionInfo()
R version 3.3.1 (2016-06-21)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)
>>locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C LC_TIME=English_United States.1252
>>attached base packages:
[1] stats graphics grDevices utils datasets methods base
>>other attached packages:
[1] survival_2.39-4 SIS_0.8-3 glmnet_2.0-5 foreach_1.4.3 Matrix_1.2-6
>>loaded via a namespace (and not attached):
[1] tools_3.3.1 splines_3.3.1 codetools_0.2-14 grid_3.3.1 iterators_1.0.8 ncvreg_3.6-0 lattice_0.20-33
dput(头(X)) 结构(c(0.59233888,0.300417212,0.282779258,-0.009662639, 0.081888137,0.071821141,1.891360558,1.845983014,1.223746856, 1.287132526,1.836024901,2.703559168,0.695837975,2.118960349, -0.122870706,0.640943374,0.60314327,1.60875525,-0.162463479, 0.50880747,-0.705933398,-0.525207189,0.061499562,-0.148622444, 2.040085659,2.44850466,2.112537213,1.9525211087,2.01810554, 2.066917799,1.814608165,1.233612774,1.97291466,1.864084655, 1.054360937,1.57533212,1.056160408,1.592106056,1.047701744, 0.867332419,0.725119429,1.154936732,-0.928966803,-1.23668934, -0.519206999,-1.117465097,-0.926468182,-0.954640374,-0.138661776, -0.849332404,-0.946017006,-0.732916724,-0.687440517,-0.440697106, 1.083047331,1.979894593,0.752969035,1.147822273,0.886408027, 2.131163278,0.525196698,0.324816699,0.250087633,0.32890298, 0.477833487,0.506043467,0.751508069,-0.398124408,0.1621809, -0.152152139,-0.133371371,0.002692295,-0.581221268,-0.364723157, -0.244836848,-0.412096813,0.147631864,-0.42103204,1.251728342, 0.964061631,0.421196237,0.815402852,1.048798702,0.97825866, -0.610074029,-1.136431274,-0.566921181,-0.942363558,-0.523507772, -0.733762824,2.16214487,0.535042615,1.391330567,1.749096396, 1.446797502,2.026734486,-0.297706896,-0.465151505,-0.057352555, -0.291471197,-0.273586104,-0.335041107,-0.568415985,-0.446065628, -0.50034528,-0.561282431,-0.567578705,-0.628333156,0.821088814, 0.484477502,0.538032896,0.673321778,0.261041602,0.6970898761, 0.141067158,-0.008862061,0.668023906,0.20414672,-0.504749456, 0.346613216,0.740046415,0.67125747,0.262825717,0.613090522, 0.935654097,0.471399257,0.748728938,0.090033297,0.623838432, 0.946172994,0.948270817,-0.106230375,-0.200922855,0.041747249, -0.236326799,0.620669,-0.820844846,0.941638949,-1.404803862, -1.914668627,-0.188208478,-1.608841301,-2.543121989,-1.850537147, -0.026614593,0.652418514,0.216198634,0.510370719,0.023247322, -0.036110406,-1.021471283,-1.830610159,-0.279651326,-1.415548586, -1.514134909,-1.46002938,0.234666669,-0.467504213,-0.953380117, -0.459821829,0.641920595,-0.252483099,1.029697917,-0.148317446, 1.018254091,1.027717767,-0.399991488,1.1220528467,0.723241903, 0.847692993,0.210604369,0.812817666,0.538846503,1.090122675, -0.458637715,-0.627950608,-0.484080458,-0.889860961,-0.260631824, -0.493210861,-0.125313023,0.149490041,0.437871787,0.209164447, 0.269349087,0.011880789,1.01867013,-0.763833792,0.600615844, -0.637522792,-1.144034121,-0.112848389,-0.254890347,-0.478094983, 0.045774768,-0.280454651,-0.180494541,-0.295168741,1.678047933, 1.498848215,1.640378452,1.41993218,0.999271282,1.764145631, -0.41249725,-0.403594892,0.142076483,-0.301726916,1.55677457, -0.64120271,0.639732191,1.023674271,0.507346172,0.824659283, 0.745833431,0.407673055,0.305923656,0.098890472,0.339439251, 0.163927018,0.2676584227,0.21562151,-0.245333447,-0.451487981, -0.245564664,-0.466023513,-0.136975122,-0.317257797,0.751339172, 0.249842459,0.452383246,0.53003177,-0.141238,0.404412661, 0.495766363,0.17133434,-0.245021413,0.069942656,-0.000402216, 0.290231026,-0.742926714,-1.020645488,0.027922903,-0.692160322, -1.394106904,-0.820393625,0.620477111,0.729884185,0.266710697, 0.610657035,0.547658979,0.861059854,-0.504159828,0.171472422, -0.225432199,-0.295641114,-0.870819249,0.384605782,-1.772875944, -0.829165559,-1.436890624,-1.721995696,0.117474875,-2.22845111, -1.019809058,-0.982125123,-0.768494165,-1.005338354,-1.234108037, -0.989908146,-0.256232387,-0.537223666,-0.036260806,-0.3963447, -0.737871047,-0.270846789,0.130012077,0.577909992,0.125650219, 0.282942175,0.295380552,0.398949091,0.572349466,0.524393917, -0.118631227,0.606649921,0.305708156,1.000781637,-0.215351854, -0.067675504,-0.439687925,-0.176018325,-0.326327328,-0.151682561, -0.723891962,-1.139355142,-0.678056968,-1.067849552,-0.545278057, -0.919803634,-0.458306658,-0.207156987,-0.010905471,-0.11406549, 0.662893352,-0.297267365,0.404513315,0.942493538,-0.041111605, 0.516016,0.512434381,0.587564748,-1.816899613,-2.079568264, -1.714081947,-1.869230137,-2.241438674,-1.96000547,-0.220566885, -0.630355505,-1.195108703,-1.042624664,-1.054251402,-0.029714133, 1.961411236,1.799571343,0.901389107,1.855978447,1.667380382, 2.331534735,0.351674043,0.041949388,0.580501674,0.0101066093, -0.254593836,0.579199256,-0.873388756,-0.899715023,-1.225594816, -0.894035522,-1.071167496,-0.607576421,-0.579409354,-0.42891654, -0.40419286,-0.653214594,-0.799501597,-0.830277595,0.157643458, 0.540425577,0.499780450,0.93378264,0.6648618038,0.505950367, -0.204253973,-0.438018587,-0.04058347,-0.444432807,-0.315167744, -0.28395961,1.317984171,1.118426046,1.167351777,1.289784631, 0.92997038,1.535449466,-0.21381296,-0.937682783,-0.027937067, -0.501453998,-0.068348791,-0.773133369,1.546970542,3.883867648, 0.252785234,2.637906057,0.255017128,1.118371728,1.953724702, -1.453120613,0.728825176,0.050025369,-1.887581095,0.7412023774, -0.549088772,-0.570910778,-0.420671423,-0.515175156,-0.745933557, -0.523630049,1.960533338,1.9535857703,1.210511452,2.145358887, 1.899409464,2.710823573),. Dim = c(6L,66L),. Dimnames = list( c(&#34; 1&#34;,&#34; 2&#34;,&#34; 3&#34;,&#34; 4&#34;,&#34; 5&#34;,&#34 ; 6&#34;),c(&#34; EIF4EBP1&#34;,&#34; TP53BP1&#34;, &#34; AKT1.AKT2.AKT3&#34;,&#34; AR&#34;,&#34; ATM&#34;,&#34; BAK1&#34;,&#34; BAX&#34;,& #34; BCL2&#34;,&#34; BCL2L1&#34;, &#34; CTNNB1&#34;,&#34; BID&#34;,&#34; BCL2L11&#34;,&#34; JUN&#34;,&#34; RAF1&#34;,&#34; CASP7& #34;,&#34; CAV1&#34;, &#34; CHEK1&#34;,&#34; CHEK2&#34;,&#34; BIRC2&#34;,&#34; CLDN7&#34;,&#34; COL6A1&#34;,&#34; CCNB1& #34;,&#34; CCNE1&#34;, &#34; CDH1&#34;,&#34; EGFR&#34;,&#34; ESR1&#34;,&#34; FN1&#34;,&#34; GATA3&#34;,&#34; GSK3A .GSK3B&#34;,&#34; ERBB2&#34;, &#34; ERBB3&#34;,&#34; INPP4B&#34;,&#34; MAPK8&#34;,&#34; XRCC5&#34;,&#34; MAPK1.MAPK3&#34;,&#34 ; MAP2K1&#34 ;, &#34; MRE11A&#34;,&#34; CDH2&#34;,&#34; CDKN1B&#34;,&#34; MAPK14&#34;,&#34; TP53&#34;,&#34; RPS6KB1& #34 ;, &#34; RPS6KA1&#34;,&#34; SERPINE1&#34;,&#34; PCNA&#34;,&#34; PGR&#34;,&#34; AKT1S1&#34;,&#34; PTEN& #34;,&#34; RAD50&#34;, &#34; RAD51&#34;,&#34; RB1&#34;,&#34; RPS6&#34;,&#34; SHC1&#34;,&#34; SRC&#34;,&#34; TSC2& #34;,&#34; XRCC1&#34;,&#34; YBX1&#34;, &#34; ARAF&#34;,&#34; BAD&#34;,&#34; BRCA2&#34;,&#34; CCNE2&#34;,&#34; FOXM1&#34;,&#34; GAPDH& #34;,&#34; MYH11&#34;, &#34; RAB11A.RAB11B&#34;,&#34; RBM15&#34;)))
dput(头(Y)) 结构(c(24,31,39,64,72,6,1,0,0,1,1,0),. Dim = c(6L, 2L),. Dimnames = list(c(&#34; 1&#34;,&#34; 2&#34;,&#34; 3&#34;,&#34; 4&#34;,&#34; 5&#34;,&#34; 6&#34;),c(&#34; time&#34;, &#34;状态&#34;)))