<lapply vs sapply>
lapply function always returns the result of function as a list from a list.
sapply function always returns the result of functions as a vector from a list.
> list_1=list(x=rnorm(5,0,1),y=runif(3,5,10))
> list_1
$x
[1] -0.1718824 -0.1953697 -0.3611449 1.1755966 -1.0458594
$y
[1] 7.881664 9.084847 9.950752
> list_2 = list(x = rnorm(10,0,1), y = c(rnorm(5,3,8), NA))
> list_2
$x
[1] 1.76547974 -0.74886117 -1.14383381 0.73317284 -1.18059019 0.31822345 0.03321232
[8] -1.14327293 0.28340189 0.64266838
$y
[1] 3.182408 -11.021280 10.861944 4.079862 -10.516394 NA
lapply function |
sapply function |
lapply always returns the result of function as a list. |
sapply always returns the result of function as a vector, matrix. |
> lapply(list_1, mean) $x [1] -0.119732 $y [1] 8.972421 > lapply(list_1, function(x) c(Mean = mean(x), SD = sd(x))) $x Mean SD -0.1197320 0.8065837 $y Mean SD 8.972421 1.039115 > lapply(list_2, function(x) c(Mean = mean(x, na.rm = T), SD = sd(x, na.rm = T))) $x Mean SD -0.04403995 0.98887082 $y Mean SD -0.6826919 9.6758414 |
> sapply(list_1, mean) x y -0.119732 8.972421 > sapply(list_1, function(x) c(Mean = mean(x), SD = sd(x))) x y Mean -0.1197320 8.972421 SD 0.8065837 1.039115 > sapply(list_2, function(x) c(Mean = mean(x, na.rm = T), SD = sd(x, na.rm = T))) x y Mean -0.04403995 -0.6826919 SD 0.98887082 9.6758414 |
sapply function |
sapply function(simplify=F) |
> sapply(list_1, mean) x y -0.119732 8.972421 |
> sapply(list_1,mean,simplify=FALSE) $x [1] 0.7408509 $y [1] 7.169339 |
<sapply vs mapply>
As we observe in the previous example, sapply returns a vector which is made from the function from list .
mapply function is a multivariate version of the sapply function. That is, it can contains more than two arguments.
> x1 = seq(30, 34, by = 2)
> x2 = seq(25, 35, by = 5)
the expand.grid function creates a data frame that contains a unique combination of x1 and x2.
> x1.x2 = expand.grid(x1, x2)
> x1.x2
Var1 Var2
1 30 25
2 32 25
3 34 25
4 30 30
5 32 30
6 34 30
7 30 35
8 32 35
9 34 35
[mapply function]
#<mapply to columns>
> x1 = seq(30, 34, by = 2)
> x1
[1] 30 32 34
> m.pred=function(x)(3*x+2)
> sapply(x1,m.pred). #sapply function has a variable x1 this is the comparison point between sapply and mapply.
[1] 92 98 104
>x2=seq(25,35,by=5)
> x1.x2=expand.grid(x1,x2)
> x1.x2
Var1 Var2
1 30 25
2 32 25
3 34 25
4 30 30
5 32 30
6 34 30
7 30 35
8 32 35
9 34 35
> x1.x2[,1] #first column
[1] 30 32 34 30 32 34 30 32 34
> x1.x2[,2]. #second column
[1] 25 25 25 30 30 30 35 35 35
> m.pred=function(x,y)(3*x+y)
> mapply(m.pred, x1.x2[,1], x1.x2[,2]) #element in first column as x, element in second column as y
[1] 115 121 127 120 126 132 125 131 137
> mapply(m.pred, x1.x2[1], x1.x2[2])
Var1
[1,] 115
[2,] 121
[3,] 127
[4,] 120
[5,] 126
[6,] 132
[7,] 125
[8,] 131
[9,] 137
> m.pred_2=function(x,y)((x+1)^2+y)
> mapply(m.pred_2,x1.x2[,1],x1.x2[,2]) #element in first column as x, element in second column as y
[1] 986 1114 1250 991 1119 1255 996 1124
[9] 1260
#<mapply to rows>
> x1_x2=rbind(x1,x2)
> x1_x2
[,1] [,2] [,3]
x1 30 32 34
x2 25 30 35
> m.pred=function(x,y)(x^2+10*y)
> mapply(m.pred , x1_x2[1,] , x1_x2[2,]) #element in first row as x and element of second row as y
[1] 1150 1324 1506
<t-test using mapply(student's, welch's)>
> student.t.test <- function(x1, x2) {
+ return(t.test(x1, x2, var.equal = TRUE)$p.value)
+ }
> welch.t.test<- function(x1, x2) {
+ return(t.test(x1, x2, var.equal = FALSE)$p.value)
+ }
> x = as.list(as.data.frame(matrix(rnorm(n=600, mean=10, sd=1),12,50))) |
> y = as.list(as.data.frame(matrix(rnorm(n=600, mean=10, sd=10),12,50))) |
> x $V1 [1] 10.569413 9.730193 10.129384 8.045248 9.507468 11.152292 9.693162 10.369953 [9] 11.217997 11.369700 9.747703 10.368824 $V2 [1] 9.591829 9.639191 10.430691 8.713020 9.365734 9.796357 9.470041 10.463307 [9] 10.788477 11.580841 10.189135 9.983516 $V3 [1] 8.569551 8.630170 10.002310 9.774065 9.140203 9.710049 11.473954 9.009991 [9] 11.907637 12.215771 8.916336 8.084277 $V4 [1] 9.953234 8.256620 8.853046 11.252880 11.312386 9.982500 9.641947 11.921640 [9] 9.914962 11.151792 9.055550 10.988085 $V5 [1] 11.277386 10.756478 11.347668 11.300402 8.522250 10.156227 9.100721 8.253531 [9] 9.731361 9.136377 10.641938 10.161165 $V6 [1] 8.822972 10.060470 11.258291 9.792795 9.480411 9.839450 10.681277 10.433093 [9] 9.153168 11.132416 9.885356 11.197503 $V7 [1] 11.642025 10.058930 11.168744 10.637830 8.008920 10.348190 10.393254 8.751812 [9] 10.421721 11.258496 8.643358 9.988735 $V8 [1] 8.177030 9.934701 10.019830 11.683906 10.058874 12.479540 10.229505 11.896030 [9] 10.591635 10.222968 9.793647 9.224552 $V9 [1] 8.920025 11.631117 10.144509 10.156021 9.609770 9.553515 10.333560 10.602403 [9] 8.792290 10.234035 10.136436 10.911875 $V10 [1] 8.425614 10.029266 10.326481 10.304341 10.841362 10.742419 10.239214 9.794407 [9] 9.547841 11.375985 10.204529 9.079666 $V11 [1] 10.769752 10.343351 9.666470 11.934241 10.179899 8.424407 10.385962 8.215562 [9] 10.711800 9.973383 10.488631 11.250497 $V12 [1] 9.402043 9.545587 10.844684 11.157446 9.049619 9.690360 9.526292 10.989130 [9] 9.652494 9.387936 9.706570 11.099918 $V13 [1] 9.302132 10.202861 11.232037 10.295327 9.554729 9.921305 9.748471 8.983887 [9] 9.438730 11.510385 10.673881 10.487738 $V14 [1] 12.624131 11.070730 9.750799 9.722343 12.088167 12.996310 10.399936 8.711927 [9] 10.204732 10.517572 10.600516 9.983142 $V15 [1] 10.373477 9.490030 10.621390 9.769112 9.968036 9.159318 10.502239 9.609087 [9] 9.115170 9.586645 10.442900 8.842283 $V16 [1] 10.432843 10.901414 8.200111 9.305012 10.469562 11.607875 10.198993 10.863067 [9] 10.353409 12.341936 8.662304 10.403412 $V17 [1] 10.229715 10.721323 8.638300 9.386579 8.781183 9.698624 10.652363 9.983659 [9] 9.980578 10.092645 10.939571 8.809258 $V18 [1] 10.194143 11.651591 9.564575 10.406631 8.297892 9.476400 10.100086 9.296703 [9] 10.338661 10.871579 10.300629 10.612365 $V19 [1] 8.873063 9.931815 10.011985 10.040373 9.910884 8.004362 8.920872 9.966077 [9] 10.515311 10.406475 10.128113 10.299180 $V20 [1] 10.236077 8.735121 9.353080 9.856171 9.138792 7.821223 10.066676 10.317724 [9] 11.221044 10.194843 10.835882 11.368091 $V21 [1] 12.008723 9.114673 7.860459 9.309153 12.405971 9.810744 11.489657 8.588896 [9] 10.522564 10.528186 8.996779 9.577241 $V22 [1] 9.967495 8.836300 10.312496 9.412208 10.921231 9.930687 9.739548 7.510454 [9] 9.851273 10.613795 10.046548 7.288920 $V23 [1] 9.560169 10.533577 8.532837 9.439206 8.504566 8.613054 9.732412 11.552097 [9] 9.315848 10.780875 10.590293 10.479729 $V24 [1] 10.726895 9.868978 11.222230 9.938351 9.568987 9.425167 11.220548 8.297832 [9] 10.969417 9.788625 11.117416 8.255932 $V25 [1] 8.245885 11.036732 9.128759 10.349829 11.268845 9.701727 9.245582 8.510485 [9] 10.564797 10.332632 10.307935 10.178132 $V26 [1] 8.414678 10.296711 9.931577 10.990956 8.849011 11.733697 11.076057 10.510635 [9] 10.980403 10.690568 10.126082 9.974705 $V27 [1] 9.504747 11.394600 10.203338 10.212920 11.993722 8.416459 7.522640 10.195159 [9] 8.162564 8.380668 11.487150 10.973510 $V28 [1] 9.616056 9.051915 9.849974 8.200029 11.187892 9.792710 9.067202 9.443566 [9] 10.875986 10.088456 10.002565 9.009843 $V29 [1] 11.661979 9.914841 11.834506 9.788110 9.832921 10.568216 11.179088 11.446190 [9] 10.867388 8.008688 10.396959 11.227422 $V30 [1] 8.966381 9.331055 9.933053 10.745908 10.915905 11.875415 9.168041 9.934039 [9] 11.021574 9.347111 8.603004 11.256605 $V31 [1] 10.820390 9.861693 9.448015 11.314620 9.408272 11.959150 8.651807 11.955363 [9] 8.992959 8.952279 11.771601 9.562229 $V32 [1] 10.889923 9.804776 10.707593 9.996622 9.684147 10.276712 10.446140 9.385195 [9] 8.584946 11.293675 10.706834 11.036381 $V33 [1] 8.780660 11.306854 9.238334 10.746422 9.898093 11.656677 9.461758 11.092331 [9] 10.938518 8.367700 10.352973 8.367915 $V34 [1] 8.924215 9.194572 10.106072 10.210378 9.175591 9.413795 11.740399 10.638750 [9] 10.305073 11.223488 10.895922 9.463377 $V35 [1] 10.051645 9.086643 10.508699 8.180019 11.646602 10.020107 9.353698 10.750617 [9] 10.031351 11.216116 9.282011 10.722776 $V36 [1] 9.816137 10.599976 9.385796 8.521524 9.407166 10.988144 11.455262 10.148820 [9] 9.580258 9.455175 9.734448 8.674892 $V37 [1] 9.593316 9.997669 9.558957 11.076040 9.605183 9.179733 10.895369 10.643794 [9] 9.516408 10.692357 9.589148 10.123699 $V38 [1] 10.494317 9.422831 10.488669 8.966916 12.311095 10.468764 9.969253 10.154723 [9] 11.111244 9.104623 10.872649 9.529517 $V39 [1] 11.422475 9.948190 10.156749 11.122148 10.667450 9.228860 11.214646 8.159029 [9] 10.429625 8.060370 10.869972 10.808402 $V40 [1] 11.307840 10.074630 8.961456 9.462628 10.024067 10.316038 10.391914 9.099028 [9] 10.861027 10.216991 10.563809 10.299955 $V41 [1] 10.995194 9.757476 10.953527 9.579378 8.646744 8.652240 10.569014 10.140191 [9] 8.769270 10.293096 10.876544 11.204256 $V42 [1] 9.638297 9.859206 9.043634 9.669574 10.191488 11.236970 9.020469 10.857576 [9] 9.227174 10.051267 10.383126 10.176865 $V43 [1] 10.625591 10.216699 12.170783 7.978018 10.306694 10.822960 8.558889 10.093585 [9] 9.478182 9.679941 9.715513 9.646146 $V44 [1] 9.595969 8.790846 10.886678 10.862796 11.011536 11.121877 9.905381 9.105809 [9] 8.273068 9.838949 11.949689 10.822118 $V45 [1] 11.136599 10.048403 9.550736 9.187555 9.658043 10.445020 8.951360 9.791721 [9] 10.311228 10.037643 9.793993 9.110682 $V46 [1] 8.687501 11.147423 9.972880 10.066211 10.546771 9.062599 10.635468 10.232013 [9] 11.345625 9.990024 9.991407 10.476954 $V47 [1] 11.133615 9.795635 10.573759 9.865851 11.020739 9.984559 8.905284 10.082623 [9] 9.308204 9.585267 10.483927 9.061792 $V48 [1] 11.527897 9.306541 9.817261 10.011999 9.647924 11.488066 9.909529 9.189852 [9] 10.384165 8.847272 9.021574 9.295149 $V49 [1] 10.580548 10.410334 9.141755 9.951232 9.310824 9.530982 9.514146 10.353115 [9] 9.172790 9.224184 9.246535 10.183254 $V50 [1] 8.476810 9.866948 12.473140 11.096465 8.835443 8.791541 11.349148 9.490491 [9] 11.766662 10.116328 8.698522 9.831709 |
> y $V1 [1] 4.015339 5.863456 10.908589 16.644048 3.586415 10.785211 15.952171 13.991881 [9] -2.047566 14.037543 11.846166 4.204510 $V2 [1] 11.5986050 11.1223394 4.3330926 11.9858945 3.0683900 0.4285652 5.6664773 11.0655365 [9] 12.6441090 15.1575612 6.5604673 -6.8845891 $V3 [1] 30.4858090 19.1903651 10.9587311 8.2432549 -2.1673356 19.6196732 21.0797542 12.1874175 [9] 10.2624958 34.5674170 16.4012723 0.2746374 $V4 [1] 6.054465 11.730736 9.178165 9.099751 5.286706 23.863680 5.763717 7.194635 [9] -4.832662 15.415662 12.340102 5.348945 $V5 [1] 9.682130 10.843301 7.659834 7.990530 -1.089217 17.949386 15.419049 13.359985 [9] 15.980861 7.315910 5.625492 1.784369 $V6 [1] 13.900792 -2.910538 -9.919566 11.619934 26.192403 11.005697 -8.028859 23.901832 [9] 19.566231 11.123783 14.637008 22.947309 $V7 [1] -13.794547 10.694331 -3.907253 10.221121 4.812186 30.336466 11.063367 5.713170 [9] 10.906563 3.632984 19.062994 18.102237 $V8 [1] 4.787456 -6.452299 23.702568 4.457065 11.418634 24.690993 10.892473 7.564364 [9] 19.309754 12.026594 10.162080 -4.146879 $V9 [1] 19.3681985 9.6962903 8.7613117 12.4783745 0.8971538 1.1631567 7.3246943 -4.2367523 [9] 23.4928584 19.8231020 0.9434693 -5.7387309 $V10 [1] -2.601023 10.375973 4.072120 -1.041408 19.124369 3.708078 16.514137 13.783774 [9] 7.323494 22.486926 5.465823 5.393504 $V11 [1] -0.2304685 6.3210024 10.9050876 0.9090195 12.8595414 1.8908955 0.1926135 9.5605253 [9] 29.2307425 4.1334189 -6.1377370 -7.8801280 $V12 [1] 20.93814 20.52897 8.46568 15.02737 -15.46326 36.19455 10.84032 23.75677 [9] 11.99185 -1.80848 26.69742 3.16329 $V13 [1] -8.444247 25.249788 -5.560716 14.011757 26.763728 9.060486 7.472202 21.207492 [9] 6.790208 18.277567 1.312642 16.582461 $V14 [1] 6.729204 33.362427 14.975839 9.025557 15.075072 -1.401448 10.169859 29.078613 [9] 14.226905 17.111919 10.223668 18.205455 $V15 [1] 21.429204 4.792800 1.191150 5.000242 8.330349 20.860509 11.472054 15.358397 [9] 30.192352 5.099775 22.224800 12.528505 $V16 [1] 25.3787078 8.8446262 19.8046995 8.3737244 3.0188198 0.5523626 1.7609299 10.8312218 [9] 12.0730519 6.7727430 7.4409260 0.2973466 $V17 [1] 6.0259098 -0.4754578 -8.1903543 0.1367535 5.4369173 6.0599242 10.8375439 2.3189462 [9] 14.8567119 0.8194798 9.2698450 16.9552743 $V18 [1] 15.742577 8.428059 2.246061 21.353946 16.992469 11.323058 23.668209 8.963437 [9] 15.292405 4.366503 13.281732 22.160906 $V19 [1] 4.611771 28.912725 24.868898 2.306133 8.950588 13.203968 1.262130 6.343924 [9] 17.138957 11.822286 21.136370 -3.111609 $V20 [1] 5.288301 8.695623 4.804431 4.555413 22.880971 10.912213 23.257241 -5.402096 [9] 2.302810 22.612287 10.409988 18.802694 $V21 [1] -6.2579628 4.1270881 15.8606239 -6.7518116 9.7867791 0.6013151 7.2975043 0.8923786 [9] -1.8095508 0.8594594 8.6777588 -1.5276333 $V22 [1] -0.5708967 13.4007552 15.7077921 11.3821379 13.9931414 24.5090773 20.8600907 -1.2247375 [9] 12.3967146 -2.5243487 5.9970236 17.4002066 $V23 [1] -0.42683043 24.85363078 11.18878137 10.49271625 12.82233140 0.06077157 18.80549356 [8] 27.59220149 8.19065299 15.90782718 11.26396551 22.41196571 $V24 [1] 32.2810974 23.9011709 11.8395955 9.4506041 27.1290118 18.9934731 0.2142779 -1.9449838 [9] 15.4151122 0.3650899 13.8123986 -1.5743000 $V25 [1] 10.577671 28.820320 17.885290 7.200444 7.233581 12.289848 25.572240 5.709248 [9] 9.194635 15.066344 10.617179 6.084928 $V26 [1] 11.1974971 -3.0508592 23.6032376 6.8238333 1.3555739 0.5371902 8.4139199 8.7051044 [9] 23.6246937 -9.2808928 9.2700703 2.7369446 $V27 [1] 30.54744537 21.49325127 21.63305774 5.47907273 14.33300899 28.94689691 14.25163854 [8] -1.37666446 -0.37235904 -1.81846735 -0.03074614 -0.09997145 $V28 [1] 0.53883912 -12.84096408 5.66896018 20.75801959 5.94356673 12.29496685 [7] 12.94618446 12.48505381 13.22907720 3.63725538 8.94735937 0.09460342 $V29 [1] 14.476896 14.038098 -6.286876 24.519986 16.396755 21.899095 16.508566 31.706405 [9] -7.918906 -5.683970 10.341391 3.855630 $V30 [1] 17.715335 11.791195 -2.083117 9.920530 10.919970 8.534892 9.867478 10.171304 [9] 16.369495 19.970167 -10.453982 9.251442 $V31 [1] 11.499897 20.544346 4.214543 13.938855 9.317015 13.061276 11.935922 33.982170 [9] 18.017044 7.480648 17.093596 -9.650853 $V32 [1] 15.581910 26.902214 13.590948 21.829779 6.648315 5.067585 -1.534243 5.706446 [9] 23.454143 5.770701 11.523554 27.962010 $V33 [1] 13.227351 -4.012569 25.896155 17.937642 -2.806699 13.902012 -1.292573 8.688711 [9] 11.587781 11.193510 6.469587 21.794832 $V34 [1] 19.4953104 5.9847500 0.4578837 13.6318392 22.6749570 24.8941531 10.6461320 22.6149657 [9] -6.4390942 16.7477986 12.4009381 6.6352061 $V35 [1] 16.334303 7.703884 11.908885 11.081741 22.987037 28.999834 17.358304 19.979099 [9] 20.943119 4.879662 6.063903 -1.178533 $V36 [1] 36.10414500 26.81472705 7.66482933 25.88972804 4.41133865 27.19378410 16.12016590 [8] 10.16358777 5.30536966 0.08887342 7.04383230 6.66144651 $V37 [1] 25.702518 8.706405 22.710031 5.939753 9.920586 13.883827 14.162927 11.574126 [9] 3.587398 -14.062540 10.022890 -3.010528 $V38 [1] 21.076250 12.379459 8.545778 15.622820 17.357709 3.149344 12.160667 14.323726 [9] 9.287955 -12.775065 7.984152 19.870589 $V39 [1] 4.084537 9.693435 8.857421 10.968986 5.266574 19.282237 14.664454 5.327032 [9] 16.187388 14.718182 14.401287 -3.881021 $V40 [1] -3.594429 25.658788 5.943731 13.969313 13.128365 17.669600 7.319379 12.840996 [9] -22.162300 -4.177205 1.485843 2.914564 $V41 [1] 12.5215938 6.6157735 8.4115957 29.4366744 12.7680246 14.7404795 17.1023654 25.0834331 [9] 10.7555553 12.2302676 0.6136142 6.6214011 $V42 [1] 8.228548 4.653852 12.074326 -6.028216 -9.597958 1.542291 22.255133 -5.294395 [9] 7.471434 19.912171 12.737261 8.036197 $V43 [1] 7.930296 20.597610 -23.531257 11.051889 11.815925 2.729325 19.359914 7.841552 [9] 0.266610 -2.986458 -1.040779 5.632739 $V44 [1] 13.208630 4.151750 8.185622 -11.437754 25.911352 10.662108 17.971363 15.997452 [9] 5.932255 5.357202 18.410557 -18.320663 $V45 [1] 10.8752685 12.9495408 10.1223555 18.8015953 0.6473604 18.5797345 3.2061320 12.1588838 [9] 14.7871615 14.9342139 -1.8500967 11.0448853 $V46 [1] 19.268465 24.518172 32.417861 12.077448 -8.860945 4.503570 25.000839 15.574787 [9] 12.216558 23.493042 30.192421 -4.288804 $V47 [1] 3.105692 9.572717 19.784026 36.401833 21.147042 -6.880582 9.326402 6.731020 [9] 10.579794 8.293651 1.755853 14.168061 $V48 [1] 26.7365770 27.8233754 0.0390809 10.2331010 1.0773903 -10.5873595 -5.4538429 [8] -14.7121663 15.2869994 8.4937058 16.3504856 3.4384350 $V49 [1] 19.343466 7.007271 18.322945 28.596038 3.177361 15.723957 11.032964 21.648590 [9] -5.787497 20.536615 15.388139 6.185372 $V50 [1] -0.4029766 10.3815105 4.9058726 22.7198265 10.2211394 25.1476328 6.2523218 20.0850280 [9] 17.9115040 24.8888563 25.5538003 1.0639196 |
extract p.value from results of the two-sample t-tests
- do student's t-test, which is two-sample t test assuming two groups has same variance, to test if the two groups have the same mean value or not for each pair of vectors in x,y.
> student.out = mapply(student.t.test, x, y)
> student.out
V1 V2 V3 V4 V5 V6 V7
0.563022081 0.144909548 0.108172703 0.519068519 0.701204745 0.773647965 0.715398189
V8 V9 V10 V11 V12 V13 V14
0.863028497 0.427205171 0.557701219 0.092238646 0.411550907 0.776526786 0.156699263
V15 V16 V17 V18 V19 V20 V21
0.199343205 0.494011158 0.039083212 0.089387203 0.561065727 0.760924039 0.001237934
V22 V23 V24 V25 V26 V27 V28
0.587839057 0.154551151 0.475907512 0.171426717 0.253470402 0.738496194 0.292089718
V29 V30 V31 V32 V33 V34 V35
0.874044616 0.757006906 0.434279888 0.250515636 0.943289115 0.402992619 0.142474222
V36 V37 V38 V39 V40 V41 V42
0.181966326 0.761334561 0.848560123 0.913061714 0.253963569 0.202944628 0.222228205
V43 V44 V45 V46 V47 V48 V49
0.155193494 0.554371297 0.724748215 0.172569993 0.714074841 0.407738784 0.189612224
V50
0.174348946
> sum(student.out < 0.05)/600
[1] 0.003333333
do welch's t-test, which is two-sample t test assuming two groups has different variance, to test if the two groups have the same mean value or not for each pair of vectors in x,y.
> welch.out=mapply(welch.t.test,x,y)
> welch.out
V1 V2 V3 V4 V5 V6 V7
0.568358090 0.158095795 0.121317301 0.525056819 0.704396849 0.776290911 0.718745087
V8 V9 V10 V11 V12 V13 V14
0.864512335 0.435463845 0.563436255 0.105464128 0.420255744 0.779130694 0.169579159
V15 V16 V17 V18 V 19 V20 V21
0.212368216 0.500536645 0.050037938 0.102360810 0.566846588 0.763644531 0.003034717
V22 V23 V24 V25 V26 V27 V28
0.592943775 0.167751387 0.483169957 0.184274339 0.265253913 0.741481401 0.303094093
V29 V30 V31 V32 V33 V34 V35
0.875448707 0.759740310 0.442144866 0.262493876 0.943893212 0.411680263 0.155760662
V36 V37 V38 V39 V40 V41 V42
0.195201605 0.764146122 0.850234924 0.913935997 0.266036722 0.215418883 0.234836241
V43 V44 V45 V46 V47 V48 V49
0.168598836 0.560220106 0.727983598 0.186050504 0.717515047 0.416484219 0.202854879
V50
0.187027273
> sum(welch.out<0.05)/600
[1] 0.001666667
'R' 카테고리의 다른 글
| (R) split function/ sapply--> tapply (0) | 2020.11.17 |
|---|---|
| (R) tapply function/ comparision to aggregate function /permutation test with tapply function (0) | 2020.11.17 |
| (R) apply function on matrix and data frame (0) | 2020.11.15 |
| (R) functions for tables/ table(), ftable(),addmargins(), prop.table(), margin.table() (0) | 2020.11.08 |
| (R) Sorting vector, data frame / sort(), order(),xtfrm (0) | 2020.11.08 |
