如何在R中创建没有列和行索引的矩阵？
要创建没有列和行索引的矩阵，我们首先需要创建矩阵，然后可以使用prmatrix函数来转换没有列和行索引的矩阵，但是我们需要提供函数内部的行数。例如，如果我们有一个包含5行5列的矩阵M，则可以使用prmatrix（M，rowlab=rep（“，”5），collab=rep（“”）将其转换为没有列和行索引的矩阵，5））。
示例
M1<-matrix(rnorm(25),ncol=5) M1
输出结果
[,1] [,2] [,3] [,4] [,5] [1,] -0.3524287 0.4753824 -0.7817841 0.4452398 1.5483299 [2,] 0.7659213 0.8160877 -0.9124624 0.3859241 -0.3645244 [3,] -0.7511866 0.4664604 -2.3584599 0.2926155 0.0354159 [4,] -0.2477745 -0.7132980 -0.6503972 -0.3519619 -0.7805707 [5,] 0.5781549 -0.1417311 -0.4956891 1.1003766 0.2343090
示例
prmatrix(M1,rowlab=rep("",5),collab=rep("",5))输出结果
-0.3524287 0.4753824 -0.7817841 0.4452398 1.5483299 0.7659213 0.8160877 -0.9124624 0.3859241 -0.3645244 -0.7511866 0.4664604 -2.3584599 0.2926155 0.0354159 -0.2477745 -0.7132980 -0.6503972 -0.3519619 -0.7805707 0.5781549 -0.1417311 -0.4956891 1.1003766 0.2343090
示例
M2<-matrix(rpois(81,2),ncol=9) M2
输出结果
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [1,] 3 1 3 2 0 2 0 2 4 [2,] 3 0 1 4 0 3 2 1 2 [3,] 4 3 2 1 4 3 3 3 4 [4,] 0 2 3 3 1 2 2 3 4 [5,] 1 1 2 3 2 1 2 4 1 [6,] 2 3 0 1 1 2 4 3 2 [7,] 6 3 0 1 2 0 1 1 1 [8,] 6 3 3 2 5 1 0 0 0 [9,] 4 1 2 3 2 2 0 1 3
示例
prmatrix(M2,rowlab=rep("",9),collab=rep("",9))输出结果
3 1 3 2 0 2 0 2 4 3 0 1 4 0 3 2 1 2 4 3 2 1 4 3 3 3 4 0 2 3 3 1 2 2 3 4 1 1 2 3 2 1 2 4 1 2 3 0 1 1 2 4 3 2 6 3 0 1 2 0 1 1 1 6 3 3 2 5 1 0 0 0 4 1 2 3 2 2 0 1 3
示例
M3<-matrix(rexp(36,1.27),ncol=2) M3
输出结果
[,1] [,2] [1,] 1.90172301 0.17485982 [2,] 0.72992558 1.22893098 [3,] 0.34723400 0.03796494 [4,] 0.03941449 1.95001158 [5,] 1.04126572 1.14392629 [6,] 0.25201154 0.57012496 [7,] 1.30187720 0.96230866 [8,] 1.13920057 1.40368354 [9,] 1.41180402 0.12139199 [10,] 0.53137688 0.01768795 [11,] 0.05370309 1.69081321 [12,] 1.13580395 0.11810967 [13,] 0.56185639 1.44204980 [14,] 1.51025894 0.23696430 [15,] 1.26819806 0.07203026 [16,] 0.30501141 0.14618651 [17,] 0.93060957 0.07317170 [18,] 0.92067027 0.08642117
示例
prmatrix(M3,rowlab=rep("",18),collab=rep("",18))输出结果
1.90172301 0.17485982 0.72992558 1.22893098 0.34723400 0.03796494 0.03941449 1.95001158 1.04126572 1.14392629 0.25201154 0.57012496 1.30187720 0.96230866 1.13920057 1.40368354 1.41180402 0.12139199 0.53137688 0.01768795 0.05370309 1.69081321 1.13580395 0.11810967 0.56185639 1.44204980 1.51025894 0.23696430 1.26819806 0.07203026 0.30501141 0.14618651 0.93060957 0.07317170 0.92067027 0.08642117
示例
M4<-matrix(runif(40,2,5),nrow=20) M4
输出结果
[,1] [,2] [1,] 2.884068 2.732077 [2,] 3.694684 2.517772 [3,] 4.165912 3.924986 [4,] 3.752682 2.414989 [5,] 3.199349 4.666055 [6,] 2.365035 3.800645 [7,] 3.121915 2.395140 [8,] 2.147690 2.463121 [9,] 4.697216 4.965934 [10,] 2.094644 4.681206 [11,] 4.071888 2.360031 [12,] 3.047279 2.485864 [13,] 2.921051 4.556291 [14,] 4.655183 4.367924 [15,] 4.727901 3.647091 [16,] 4.807526 4.086226 [17,] 2.193533 2.246970 [18,] 3.198273 3.197613 [19,] 2.371362 3.260453 [20,] 4.070255 3.981377
示例
prmatrix(M4,rowlab=rep("",20),collab=rep("",20))输出结果
2.884068 2.732077 3.694684 2.517772 4.165912 3.924986 3.752682 2.414989 3.199349 4.666055 2.365035 3.800645 3.121915 2.395140 2.147690 2.463121 4.697216 4.965934 2.094644 4.681206 4.071888 2.360031 3.047279 2.485864 2.921051 4.556291 4.655183 4.367924 4.727901 3.647091 4.807526 4.086226 2.193533 2.246970 3.198273 3.197613 2.371362 3.260453 4.070255 3.981377
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