How to divide the matrix rows by row standard deviation in R?

R Programming Server Side Programming Programming

To divide matrix row values by row standard deviation in R, we can follow the below steps −

First of all, create a matrix.
Then, use apply function to divide the matrix row values by row standard deviation.

Create the matrix

Let's create a matrix as shown below −

M<-matrix(sample(1:1000,100),ncol=4)
M

On executing, the above script generates the below output(this output will vary on your system due to randomization) −

      [,1] [,2] [,3] [,4]
[1,]  651  787  927   842
[2,]  9    633  698   445
[3,]  661  536  794   680
[4,]  910  396  814   91
[5,]  716  838  253   239
[6,]  227  547  754   371
[7,]  122  84   236   745
[8,]  992  969  348   523
[9,]  281  623  209   957
[10,] 415  453  578   827
[11,] 452  225  294   419
[12,] 796  675  321   41
[13,] 614  213  473   526
[14,] 392  447  652   50
[15,] 946  460  561   724
[16,] 362  108  571   594
[17,] 898  829  535   318
[18,] 994  951  988   938
[19,] 270  45   591   74
[20,] 840  5    154   470
[21,] 329  820  481   85
[22,] 297  906  265   932
[23,] 471  282  256   436
[24,] 434  425  13    36
[25,] 627  200  815 784

Divide the matrix row values by row standard deviation

Using apply function to divide the row values of M by row standard deviation −

Live Demo

M<-matrix(sample(1:1000,100),ncol=4)
M_new<-t(apply(M,1, function(x) x/sd(x)))
M_new

Output

         [,1]        [,2]       [,3]        [,4]
[1,]  5.62023697  6.79435714  8.00301025  7.2691851
[2,]  0.02897489  2.03790061  2.24716371  1.4326473
[3,]  6.25585513  5.07282655  7.51459754  6.4356755
[4,]  2.39345882  1.04154911  2.14096207  0.2393459
[5,]  2.30488157  2.69761279  0.81443441  0.7693669
[6,]  0.99755809  2.40380738  3.31347488  1.6303703
[7,]  0.39904046  0.27474917  0.77191433  2.4367635
[8,]  3.07309809  3.00184683  1.07806264  1.6201918
[9,]  0.81641559  1.81006019  0.60722726  2.7804616
[10,] 2.23089532  2.43517007  3.10712650  4.4456637
[11,] 4.25199561  2.11659074  2.76567856  3.9415623
[12,] 2.31727586  1.96502664  0.93447934  0.1193572
[13,] 3.56077176  1.23525144  2.74307010  3.0504331
[14,] 1.56839005  1.78844478  2.60864876 0.2000498
[15,] 4.45878085  2.16811754  2.64416074 3.4124285
[16,] 1.60150472  0.47779699  2.52613037 2.6278834
[17,] 3.33974413  3.08312682  1.98971393 1.1826711
[18,] 36.17736050 34.61234390 35.95898609 34.1391993
[19,] 1.07405332  0.17900889  2.35098337 0.2943702
[20,] 2.27013002  0.01351268  0.41619050 1.2701918
[21,] 1.06944378  2.66548298  1.56353331 0.2763001
[22,] 0.80545896  2.45705663  0.71867550 2.5275682
[23,] 4.36118901  2.61115775  2.37041271 4.0371091
[24,] 1.85435094  1.81589666  0.05554507 0.1538171
[25,] 2.21382535  0.70616439  2.87761987 2.7681644

Nizamuddin Siddiqui

Published on 09-Aug-2021 08:30:09

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