predict.glmnet.RdSimilar to other predict methods, this functions predicts fitted values,
logits, coefficients and more from a fitted "glmnet" object.
# S3 method for glmnet coef(object, s = NULL, exact = FALSE, ...) # S3 method for glmnet predict(object, newx, s = NULL, type = c("link", "response", "coefficients", "nonzero", "class"), exact = FALSE, newoffset, ...) # S3 method for relaxed predict(object, newx, s = NULL, gamma = 1, type = c("link", "response", "coefficients", "nonzero", "class"), exact = FALSE, newoffset, ...)
| object | Fitted |
|---|---|
| s | Value(s) of the penalty parameter |
| exact | This argument is relevant only when predictions are made at
values of |
| ... | This is the mechanism for passing arguments like |
| newx | Matrix of new values for |
| type | Type of prediction required. Type |
| newoffset | If an offset is used in the fit, then one must be supplied
for making predictions (except for |
| gamma | Single value of |
The object returned depends on type.
The shape of the objects returned are different for "multinomial"
objects. This function actually calls NextMethod(), and the
appropriate predict method is invoked for each of the three model types.
coef(...) is equivalent to predict(type="coefficients",...)
Friedman, J., Hastie, T. and Tibshirani, R. (2008)
Regularization Paths for Generalized Linear Models via Coordinate
Descent, https://web.stanford.edu/~hastie/Papers/glmnet.pdf
Journal of Statistical Software, Vol. 33(1), 1-22 Feb 2010
https://www.jstatsoft.org/v33/i01/
Simon, N., Friedman, J., Hastie,
T., Tibshirani, R. (2011) Regularization Paths for Cox's Proportional
Hazards Model via Coordinate Descent, Journal of Statistical Software, Vol.
39(5) 1-13
https://www.jstatsoft.org/v39/i05/
glmnet, and print, and coef methods, and
cv.glmnet.
x=matrix(rnorm(100*20),100,20) y=rnorm(100) g2=sample(1:2,100,replace=TRUE) g4=sample(1:4,100,replace=TRUE) fit1=glmnet(x,y) predict(fit1,newx=x[1:5,],s=c(0.01,0.005))#> 1 2 #> [1,] -0.3037893 -0.3067493 #> [2,] -0.5245809 -0.5450835 #> [3,] -0.6210713 -0.6606625 #> [4,] -0.9940492 -1.0306614 #> [5,] -1.0283366 -1.0802449#> 21 x 66 sparse Matrix of class "dgCMatrix"#>#> #> (Intercept) -0.05700824 -0.05779938 -0.05852023 -0.05917704 -0.05894747 #> V1 . . . . . #> V2 . . . . . #> V3 . . . . 0.01192345 #> V4 . . . . . #> V5 . . . . . #> V6 . . . . . #> V7 . . . . . #> V8 . 0.02169936 0.04147101 0.05948620 0.07579326 #> V9 . . . . . #> V10 . . . . . #> V11 . . . . . #> V12 . . . . . #> V13 . . . . . #> V14 . . . . . #> V15 . . . . . #> V16 . . . . . #> V17 . . . . . #> V18 . . . . . #> V19 . . . . . #> V20 . . . . . #> #> (Intercept) -0.058202084 -0.05699762 -0.05576873 -0.05437576 -0.05301113 #> V1 . . . . . #> V2 . . . . . #> V3 0.026309528 0.03933279 0.05139986 0.06281234 0.07333608 #> V4 . . . . . #> V5 0.004265424 0.01592085 0.02691299 0.03770242 0.04760766 #> V6 . . . . . #> V7 . . . . . #> V8 0.090425233 0.10340365 0.11470810 0.12392501 0.13194059 #> V9 . . . . . #> V10 . . . . . #> V11 . . . . . #> V12 . . . . . #> V13 . . . . . #> V14 . . . . . #> V15 . . . . . #> V16 . . . . . #> V17 . . . . . #> V18 . . . . . #> V19 . . 0.00390379 0.01557760 0.02632822 #> V20 . . . . 0.00143025 #> #> (Intercept) -0.051589299 -0.050432168 -0.050036979 -0.049648523 -0.049084886 #> V1 . . . . . #> V2 0.005104009 0.012505657 0.018755404 0.023811633 0.027886196 #> V3 0.083555283 0.094000231 0.102053383 0.110616948 0.118821633 #> V4 . . . . . #> V5 0.056821669 0.064074257 0.069924143 0.075115984 0.079076108 #> V6 . . . . . #> V7 . . . . . #> V8 0.136323446 0.141263547 0.148149468 0.155112894 0.162545754 #> V9 . -0.008062357 -0.016331029 -0.024696630 -0.032592768 #> V10 . . . . . #> V11 . . . -0.005108487 -0.012105424 #> V12 . . . . . #> V13 . . . . . #> V14 . . . . . #> V15 . . . . . #> V16 . . . . 0.003404985 #> V17 . -0.001323090 -0.008541288 -0.014925122 -0.021445394 #> V18 . . . . . #> V19 0.036702802 0.046021797 0.054548265 0.061753028 0.068076131 #> V20 0.010076412 0.017845184 0.024859686 0.031228923 0.036994926 #> #> (Intercept) -0.048942459 -0.048105605 -0.04722324 -0.04642121 -0.04569051 #> V1 . . . . . #> V2 0.033160730 0.037926422 0.04232308 0.04631477 0.04995122 #> V3 0.126038430 0.132757657 0.13896806 0.14461206 0.14975408 #> V4 . . . . . #> V5 0.082600505 0.086333178 0.08985103 0.09304582 0.09595652 #> V6 . -0.006723596 -0.01392109 -0.02048127 -0.02645833 #> V7 . . . . . #> V8 0.167931948 0.172075272 0.17563993 0.17891946 0.18190836 #> V9 -0.039739925 -0.046311451 -0.05234424 -0.05783532 -0.06283825 #> V10 . . . . . #> V11 -0.018844972 -0.025708258 -0.03210518 -0.03793294 -0.04324265 #> V12 . . . . . #> V13 . . . . . #> V14 -0.006844741 -0.014246723 -0.02118482 -0.02750259 -0.03325876 #> V15 . . . . . #> V16 0.007467640 0.010312351 0.01272353 0.01493303 0.01694671 #> V17 -0.027905823 -0.034525429 -0.04061302 -0.04617594 -0.05124516 #> V18 . . . . . #> V19 0.074236479 0.079247134 0.08372532 0.08780104 0.09151466 #> V20 0.042046564 0.047057620 0.05170231 0.05592920 0.05978049 #> #> (Intercept) -0.04502472 -0.04441808 -0.044208940 -0.043811959 -0.043690501 #> V1 . . . . . #> V2 0.05326459 0.05628362 0.059841964 0.063877906 0.067591068 #> V3 0.15443928 0.15870826 0.162389137 0.165690887 0.168702457 #> V4 . . . . 0.001668169 #> V5 0.09860864 0.10102514 0.102873950 0.104374878 0.105817359 #> V6 -0.03190440 -0.03686664 -0.041481464 -0.045425422 -0.048959556 #> V7 . . 0.003260545 0.006488219 0.009738234 #> V8 0.18463175 0.18711321 0.189432053 0.191489475 0.193070434 #> V9 -0.06739672 -0.07155023 -0.075213611 -0.079011536 -0.082669706 #> V10 . . . . . #> V11 -0.04808065 -0.05248885 -0.056792603 -0.061098107 -0.064880130 #> V12 . . . . . #> V13 . . . . . #> V14 -0.03850356 -0.04328242 -0.047613236 -0.051684965 -0.055314915 #> V15 . . 0.001511234 0.006218936 0.010658444 #> V16 0.01878151 0.02045331 0.021750601 0.022850054 0.023487348 #> V17 -0.05586405 -0.06007261 -0.063756525 -0.067061393 -0.069897526 #> V18 . . . . . #> V19 0.09489837 0.09798148 0.100898753 0.103423730 0.105622400 #> V20 0.06328964 0.06648705 0.069357217 0.071889223 0.074098109 #> #> (Intercept) -0.043283408 -0.042860610 -0.042478736 -0.042349076 -0.0422643154 #> V1 . . . . . #> V2 0.071192849 0.074414671 0.077376853 0.080171274 0.0827635453 #> V3 0.171389215 0.173793096 0.176005556 0.178101837 0.1798873447 #> V4 0.002713922 0.003497324 0.004237230 0.005106450 0.0060802477 #> V5 0.107135170 0.108328028 0.109417476 0.110583216 0.1116292825 #> V6 -0.052490302 -0.055741202 -0.058704415 -0.061548625 -0.0641320246 #> V7 0.012883924 0.015748698 0.018362332 0.020905283 0.0232934375 #> V8 0.194239117 0.195338436 0.196319808 0.197255617 0.1979628699 #> V9 -0.085768594 -0.088511499 -0.091032929 -0.093554477 -0.0959811826 #> V10 . . . 0.002633589 0.0050813248 #> V11 -0.068321675 -0.071427707 -0.074271576 -0.076633795 -0.0788045123 #> V12 . . . . . #> V13 . . . . 0.0008893557 #> V14 -0.058702471 -0.061767256 -0.064569128 -0.066974357 -0.0693027303 #> V15 0.014576792 0.018098929 0.021318825 0.024124799 0.0266225024 #> V16 0.024132626 0.024796350 0.025379209 0.025926687 0.0264065920 #> V17 -0.072558971 -0.075048863 -0.077295713 -0.079723169 -0.0819143947 #> V18 -0.002401769 -0.004874331 -0.007118082 -0.008709924 -0.0100323677 #> V19 0.107911253 0.110042231 0.111979469 0.113811018 0.1154723858 #> V20 0.076403478 0.078546220 0.080496666 0.082295603 0.0838021830 #> #> (Intercept) -0.042176692 -0.042097138 -0.042024654 -0.041958610 -0.041898432 #> V1 . . . . . #> V2 0.085101374 0.087239079 0.089187171 0.090962213 0.092579566 #> V3 0.181503124 0.182975092 0.184316545 0.185538839 0.186652547 #> V4 0.006927799 0.007704112 0.008411657 0.009056355 0.009643780 #> V5 0.112566779 0.113425417 0.114207820 0.114920721 0.115570289 #> V6 -0.066452673 -0.068578438 -0.070515449 -0.072280384 -0.073888528 #> V7 0.025480467 0.027473718 0.029289896 0.030944731 0.032452555 #> V8 0.198568527 0.199120865 0.199623908 0.200082249 0.200499871 #> V9 -0.098205321 -0.100238244 -0.102090814 -0.103778818 -0.105316864 #> V10 0.007274958 0.009272502 0.011092511 0.012750833 0.014261833 #> V11 -0.080776331 -0.082584075 -0.084231404 -0.085732395 -0.087100043 #> V12 . . . . . #> V13 0.001911461 0.002844578 0.003694839 0.004469566 0.005175469 #> V14 -0.071429934 -0.073377582 -0.075152347 -0.076769454 -0.078242901 #> V15 0.028866549 0.030915477 0.032782493 0.034483652 0.036033686 #> V16 0.026859792 0.027266081 0.027636054 0.027973149 0.028280298 #> V17 -0.083891546 -0.085690726 -0.087329836 -0.088823322 -0.090184130 #> V18 -0.011233196 -0.012323939 -0.013317721 -0.014223215 -0.015048268 #> V19 0.116997713 0.118383934 0.119646960 0.120797781 0.121846366 #> V20 0.085157138 0.086389713 0.087512776 0.088536069 0.089468456 #> #> (Intercept) -0.041843600 -0.041793640 -0.041748118 -0.041706640 -0.041668846 #> V1 . . . . . #> V2 0.094053238 0.095395993 0.096619462 0.097734240 0.098749985 #> V3 0.187667317 0.188591937 0.189434417 0.190202053 0.190901495 #> V4 0.010179020 0.010666710 0.011111076 0.011515965 0.011884885 #> V5 0.116162152 0.116701435 0.117192810 0.117640532 0.118048480 #> V6 -0.075353809 -0.076688918 -0.077905420 -0.079013851 -0.080023812 #> V7 0.033826428 0.035078250 0.036218863 0.037258148 0.038205105 #> V8 0.200880393 0.201227111 0.201543027 0.201830878 0.202093157 #> V9 -0.106718274 -0.107995187 -0.109158663 -0.110218778 -0.111184716 #> V10 0.015638601 0.016893060 0.018036076 0.019077550 0.020026503 #> V11 -0.088346193 -0.089481639 -0.090516214 -0.091458881 -0.092317803 #> V12 . . . . . #> V13 0.005818662 0.006404715 0.006938705 0.007425257 0.007868584 #> V14 -0.079585452 -0.080808734 -0.081923343 -0.082938933 -0.083864301 #> V15 0.037446019 0.038732884 0.039905427 0.040973805 0.041947271 #> V16 0.028560159 0.028815159 0.029047506 0.029259211 0.029452109 #> V17 -0.091424048 -0.092553815 -0.093583216 -0.094521169 -0.095375796 #> V18 -0.015800025 -0.016484999 -0.017109121 -0.017677798 -0.018195955 #> V19 0.122801797 0.123672351 0.124465567 0.125188316 0.125846858 #> V20 0.090318012 0.091092096 0.091797413 0.092440071 0.093025637 #> #> (Intercept) -0.041634411 -0.041603034 -0.041574445 -0.041548395 -0.041524660 #> V1 . . . . . #> V2 0.099675494 0.100518784 0.101287157 0.101987271 0.102625188 #> V3 0.191538800 0.192119488 0.192648590 0.193130688 0.193569957 #> V4 0.012221031 0.012527315 0.012806389 0.013060672 0.013292364 #> V5 0.118420187 0.118758873 0.119067470 0.119348653 0.119604856 #> V6 -0.080944051 -0.081782539 -0.082546537 -0.083242664 -0.083876949 #> V7 0.039067937 0.039854118 0.040570456 0.041223157 0.041817874 #> V8 0.202332136 0.202549884 0.202748289 0.202929067 0.203093786 #> V9 -0.112064843 -0.112866781 -0.113597478 -0.114263261 -0.114869898 #> V10 0.020891153 0.021678990 0.022396837 0.023050913 0.023646883 #> V11 -0.093100422 -0.093813515 -0.094463258 -0.095055280 -0.095594709 #> V12 . . . . . #> V13 0.008272528 0.008640587 0.008975948 0.009281516 0.009559939 #> V14 -0.084707462 -0.085475719 -0.086175726 -0.086813546 -0.087394704 #> V15 0.042834258 0.043642446 0.044378838 0.045049810 0.045661175 #> V16 0.029627870 0.029788017 0.029933938 0.030066895 0.030188040 #> V17 -0.096154500 -0.096864027 -0.097510521 -0.098099582 -0.098636313 #> V18 -0.018668081 -0.019098264 -0.019490231 -0.019847376 -0.020172794 #> V19 0.126446897 0.126993630 0.127491793 0.127945700 0.128359284 #> V20 0.093559183 0.094045330 0.094488289 0.094891897 0.095259650 #> #> (Intercept) -0.0415092829 -0.041501715 -0.041499004 -0.041496756 -0.041494723 #> V1 . . . . . #> V2 0.1032457313 0.103820060 0.104351076 0.104833591 0.105273011 #> V3 0.1940317636 0.194504106 0.194925226 0.195307651 0.195655923 #> V4 0.0135248089 0.013756197 0.013964215 0.014152877 0.014324632 #> V5 0.1197850004 0.119900386 0.119988706 0.120067762 0.120139658 #> V6 -0.0844891124 -0.085066099 -0.085610072 -0.086106034 -0.086557904 #> V7 0.0424725705 0.043161986 0.043810509 0.044402262 0.044941495 #> V8 0.2033356411 0.203654027 0.203977427 0.204275635 0.204547732 #> V9 -0.1154290645 -0.115939220 -0.116403853 -0.116826363 -0.117211185 #> V10 0.0242832924 0.024947699 0.025565562 0.026129488 0.026643414 #> V11 -0.0961538057 -0.096712247 -0.097230487 -0.097702593 -0.098132679 #> V12 -0.0005085753 -0.001392721 -0.002222262 -0.002979659 -0.003669891 #> V13 0.0098387420 0.010104161 0.010347528 0.010569046 0.010770851 #> V14 -0.0878937054 -0.088307344 -0.088688210 -0.089034494 -0.089349889 #> V15 0.0462282336 0.046749390 0.047228017 0.047663926 0.048061052 #> V16 0.0303077820 0.030433978 0.030559326 0.030675164 0.030780928 #> V17 -0.0992085525 -0.099807826 -0.100375493 -0.100894930 -0.101368477 #> V18 -0.0205704994 -0.021014124 -0.021421972 -0.021793857 -0.022132744 #> V19 0.1286987247 0.128977108 0.129223516 0.129447668 0.129651893 #> V20 0.0955613298 0.095808326 0.096026168 0.096224201 0.096404609 #> #> (Intercept) -0.041492871 -0.04149118 -0.041489647 -4.149906e-02 -0.0415164791 #> V1 . . . 5.885663e-05 0.0001558716 #> V2 0.105673363 0.10603815 0.106370521 1.066747e-01 0.1069675087 #> V3 0.195973232 0.19626235 0.196525782 1.967621e-01 0.1969735052 #> V4 0.014481109 0.01462368 0.014753591 1.486451e-02 0.0149619307 #> V5 0.120205153 0.12026483 0.120319201 1.203719e-01 0.1204210283 #> V6 -0.086969625 -0.08734477 -0.087686587 -8.799753e-02 -0.0882754377 #> V7 0.045432828 0.04588051 0.046288425 4.665942e-02 0.0469972151 #> V8 0.204795699 0.20502164 0.205227513 2.054139e-01 0.2055821778 #> V9 -0.117561800 -0.11788127 -0.118172349 -1.184354e-01 -0.1186781051 #> V10 0.027111696 0.02753838 0.027927154 2.828958e-02 0.0286147663 #> V11 -0.098524545 -0.09888160 -0.099206931 -9.949943e-02 -0.0997638148 #> V12 -0.004298816 -0.00487187 -0.005394016 -5.861572e-03 -0.0062842912 #> V13 0.010954724 0.01112226 0.011274916 1.140725e-02 0.0115215295 #> V14 -0.089637249 -0.08989908 -0.090137647 -9.035188e-02 -0.0905432101 #> V15 0.048422891 0.04875258 0.049052988 4.934032e-02 0.0496175863 #> V16 0.030877323 0.03096516 0.031045190 3.112322e-02 0.0311933713 #> V17 -0.101799985 -0.10219316 -0.102551412 -1.028714e-01 -0.1031501169 #> V18 -0.022441530 -0.02272288 -0.022979245 -2.322072e-02 -0.0234442643 #> V19 0.129837976 0.13000753 0.130162016 1.302936e-01 0.1304041387 #> V20 0.096568987 0.09671876 0.096855232 9.697168e-02 0.0970693586 #> #> (Intercept) -0.0415303928 -0.0415430072 -0.0415467493 -0.0415563089 #> V1 0.0002358817 0.0003084364 0.0003709984 0.0004306885 #> V2 0.1072293146 0.1074674569 0.1076428086 0.1078394627 #> V3 0.1971680577 0.1973451062 0.1975050516 0.1976530487 #> V4 0.0150509954 0.0151320874 0.0151821407 0.0152478993 #> V5 0.1204655823 0.1205061838 0.1205614751 0.1205964889 #> V6 -0.0885300181 -0.0887620557 -0.0889367280 -0.0891273970 #> V7 0.0473044645 0.0475844508 0.0478145874 0.0480446097 #> V8 0.2057357665 0.2058758713 0.2059793617 0.2060921097 #> V9 -0.1188983600 -0.1190988348 -0.1192654269 -0.1194311406 #> V10 0.0289138341 0.0291864629 0.0294209900 0.0296463708 #> V11 -0.1000048896 -0.1002245015 -0.1004072015 -0.1005869607 #> V12 -0.0066691380 -0.0070198509 -0.0073013345 -0.0075891444 #> V13 0.0116268044 0.0117228085 0.0118156813 0.0118956880 #> V14 -0.0907182730 -0.0908777949 -0.0910119165 -0.0911436356 #> V15 0.0498664962 0.0500930788 0.0502834941 0.0504703232 #> V16 0.0312583065 0.0313176002 0.0313726810 0.0314222590 #> V17 -0.1034075248 -0.1036423599 -0.1038392814 -0.1040329146 #> V18 -0.0236476365 -0.0238329364 -0.0239982417 -0.0241525303 #> V19 0.1305071941 0.1306011846 0.1307004927 0.1307800275 #> V20 0.0971605109 0.0972436330 0.0973300182 0.0974002562 #> #> (Intercept) -0.0415663603 -0.0415757374 -0.0415843152 -0.0415921357 #> V1 0.0004857522 0.0005360629 0.0005819284 0.0006237225 #> V2 0.1080227900 0.1081903526 0.1083430853 0.1084822507 #> V3 0.1977870663 0.1979091149 0.1980203121 0.1981216272 #> V4 0.0153110126 0.0153689528 0.0154217883 0.0154699291 #> V5 0.1206260538 0.1206525132 0.1206765255 0.1206983851 #> V6 -0.0893055849 -0.0894686101 -0.0896172505 -0.0897526999 #> V7 0.0482580555 0.0484531969 0.0486311136 0.0487932433 #> V8 0.2061993504 0.2062980419 0.2063881699 0.2064703348 #> V9 -0.1195838961 -0.1197234022 -0.1198505589 -0.1199664225 #> V10 0.0298535858 0.0300426813 0.0302150265 0.0303720700 #> V11 -0.1007541326 -0.1009070614 -0.1010465023 -0.1011735697 #> V12 -0.0078569490 -0.0081019391 -0.0083253372 -0.0085289198 #> V13 0.0119679585 0.0120336888 0.0120935548 0.0121480973 #> V14 -0.0912652019 -0.0913761292 -0.0914772076 -0.0915693027 #> V15 0.0506428165 0.0508003560 0.0509439551 0.0510748037 #> V16 0.0314669845 0.0315077263 0.0315448686 0.0315787209 #> V17 -0.1042117053 -0.1043750217 -0.1045239123 -0.1046595950 #> V18 -0.0242930059 -0.0244209727 -0.0245375713 -0.0246438134 #> V19 0.1308502664 0.1309138638 0.1309717440 0.1310244716 #> V20 0.0974624671 0.0975188314 0.0975701340 0.0976168701 #> #> (Intercept) -0.0415992620 -0.0416057552 -0.0416116716 #> V1 0.0006618038 0.0006965019 0.0007281175 #> V2 0.1086090508 0.1087245853 0.1088298556 #> V3 0.1982139402 0.1982980519 0.1983746912 #> V4 0.0155137912 0.0155537557 0.0155901696 #> V5 0.1207182986 0.1207364423 0.1207529738 #> V6 -0.0898761181 -0.0899885723 -0.0900910363 #> V7 0.0489409729 0.0490755791 0.0491982274 #> V8 0.2065452101 0.2066134360 0.2066756015 #> V9 -0.1200719924 -0.1201681832 -0.1202558284 #> V10 0.0305151640 0.0306455464 0.0307643461 #> V11 -0.1012893504 -0.1013948455 -0.1014909686 #> V12 -0.0087144222 -0.0088834462 -0.0090374547 #> V13 0.0121977934 0.0122430744 0.0122843327 #> V14 -0.0916532144 -0.0917296711 -0.0917993354 #> V15 0.0511940284 0.0513026612 0.0514016433 #> V16 0.0316095693 0.0316376782 0.0316632903 #> V17 -0.1047832289 -0.1048958808 -0.1049985254 #> V18 -0.0247406180 -0.0248288229 -0.0249091921 #> V19 0.1310725136 0.1311162875 0.1311561726 #> V20 0.0976594529 0.0976982527 0.0977336055#> s0 s1 s2 s3 s4 s5 s6 s7 #> [1,] 0.49 0.4962467 0.5062733 0.5206122 0.5407381 0.5591158 0.5779415 0.5970651 #> [2,] 0.49 0.4795820 0.4706659 0.4628296 0.4560337 0.4497829 0.4480645 0.4478387 #> [3,] 0.49 0.4814987 0.4777668 0.4756991 0.4753262 0.4749664 0.4800043 0.4845192 #> [4,] 0.49 0.4862242 0.4928133 0.4974646 0.4986801 0.4997877 0.5141471 0.5285622 #> s8 s9 s10 s11 s12 s13 s14 #> [1,] 0.6212125 0.6464876 0.6716376 0.6948439 0.7124006 0.7275561 0.7437893 #> [2,] 0.4523336 0.4584540 0.4631188 0.4684622 0.4739401 0.4798677 0.4872773 #> [3,] 0.4790691 0.4664649 0.4575183 0.4522991 0.4565731 0.4602511 0.4654025 #> [4,] 0.5366545 0.5385771 0.5434832 0.5476718 0.5455655 0.5436697 0.5422430 #> s15 s16 s17 s18 s19 s20 s21 #> [1,] 0.7595146 0.7742376 0.7878513 0.8022617 0.8189572 0.8346100 0.8484135 #> [2,] 0.4946109 0.4963838 0.4944780 0.4923234 0.4851229 0.4782814 0.4719317 #> [3,] 0.4704631 0.4692565 0.4663457 0.4632768 0.4581653 0.4526547 0.4474877 #> [4,] 0.5412817 0.5420389 0.5430920 0.5450619 0.5488526 0.5547055 0.5603860 #> s22 s23 s24 s25 s26 s27 s28 #> [1,] 0.8608808 0.8719649 0.8816613 0.8901519 0.8975978 0.9041381 0.9098931 #> [2,] 0.4662941 0.4611939 0.4564759 0.4521115 0.4480772 0.4443509 0.4409117 #> [3,] 0.4413815 0.4350968 0.4292907 0.4239341 0.4189950 0.4144434 0.4102515 #> [4,] 0.5656447 0.5704850 0.5749503 0.5790711 0.5828711 0.5863727 0.5895971 #> s29 s30 s31 s32 s33 s34 s35 #> [1,] 0.9149658 0.9194454 0.9233344 0.9266993 0.9296935 0.9323620 0.9347439 #> [2,] 0.4377401 0.4348173 0.4320922 0.4295490 0.4272113 0.4250645 0.4230941 #> [3,] 0.4063932 0.4028442 0.3996101 0.3966766 0.3939826 0.3915102 0.3892422 #> [4,] 0.5925641 0.5952925 0.5977441 0.5999261 0.6019300 0.6037689 0.6054557 #> s36 s37 s38 s39 s40 s41 s42 #> [1,] 0.9368728 0.9387700 0.9404780 0.9420108 0.9433877 0.9446259 0.9457405 #> [2,] 0.4212866 0.4196292 0.4181104 0.4167192 0.4154454 0.4142795 0.4132127 #> [3,] 0.3871627 0.3852671 0.3835211 0.3819221 0.3804585 0.3791193 0.3778944 #> [4,] 0.6070021 0.6084297 0.6097271 0.6109146 0.6120014 0.6129957 0.6139050 #> s43 s44 s45 s46 s47 s48 s49 #> [1,] 0.9467448 0.9476415 0.9484593 0.9491984 0.9498665 0.9504708 0.9510178 #> [2,] 0.4122370 0.4113491 0.4105332 0.4097877 0.4091065 0.4084843 0.4079160 #> [3,] 0.3767744 0.3757621 0.3748262 0.3739705 0.3731888 0.3724749 0.3718230 #> [4,] 0.6147363 0.6155073 0.6162014 0.6168348 0.6174134 0.6179417 0.6184241 #> s50 s51 s52 s53 s54 s55 s56 #> [1,] 0.9515030 0.9519518 0.9523594 0.9527291 0.9530645 0.9533689 0.9536452 #> [2,] 0.4074076 0.4069332 0.4065001 0.4061048 0.4057440 0.4054149 0.4051147 #> [3,] 0.3712394 0.3706964 0.3701998 0.3697466 0.3693330 0.3689557 0.3686115 #> [4,] 0.6188748 0.6192771 0.6196430 0.6199767 0.6202812 0.6205590 0.6208123#> $s0 #> NULL #> #> $s1 #> [1] 19 #> #> $s2 #> [1] 17 19 #> #> $s3 #> [1] 14 17 19 #> #> $s4 #> [1] 14 17 19 #> #> $s5 #> [1] 14 17 19 #> #> $s6 #> [1] 14 17 19 20 #> #> $s7 #> [1] 3 14 17 19 20 #> #> $s8 #> [1] 3 5 14 17 19 20 #> #> $s9 #> [1] 1 3 5 14 17 19 20 #> #> $s10 #> [1] 1 3 5 14 17 19 20 #> #> $s11 #> [1] 1 3 5 7 12 14 17 19 20 #> #> $s12 #> [1] 1 3 4 5 7 12 14 17 19 20 #> #> $s13 #> [1] 1 3 4 5 7 12 14 17 19 20 #> #> $s14 #> [1] 1 3 4 5 7 8 12 14 17 19 20 #> #> $s15 #> [1] 1 3 4 5 7 8 10 12 14 17 19 20 #> #> $s16 #> [1] 1 3 4 5 7 8 10 11 12 14 17 19 20 #> #> $s17 #> [1] 1 3 4 5 7 8 9 10 11 12 14 17 19 20 #> #> $s18 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 14 17 19 20 #> #> $s19 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 14 17 19 20 #> #> $s20 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 14 15 17 19 20 #> #> $s21 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 14 15 17 19 20 #> #> $s22 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 14 15 16 17 19 20 #> #> $s23 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 14 15 16 17 19 20 #> #> $s24 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 14 15 16 17 19 20 #> #> $s25 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 14 15 16 17 19 20 #> #> $s26 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 14 15 16 17 19 20 #> #> $s27 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 14 15 16 17 19 20 #> #> $s28 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 14 15 16 17 19 20 #> #> $s29 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 14 15 16 17 19 20 #> #> $s30 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 14 15 16 17 19 20 #> #> $s31 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s32 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s33 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s34 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s35 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s36 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s37 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s38 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s39 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s40 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s41 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s42 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s43 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s44 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s45 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s46 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s47 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s48 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s49 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s50 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s51 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s52 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s53 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s54 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s55 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #> #> $s56 #> [1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 19 20 #>#> , , 1 #> #> 1 2 3 4 #> [1,] 0.2143507 0.2815262 0.11093754 0.39318563 #> [2,] 0.1603873 0.2412464 0.08515374 0.51321254 #> [3,] 0.6666361 0.0227436 0.22279029 0.08782998 #>