Randomly initializes based on ALR transform of counts plus random pseudocounts uniformily distributed between 0 and 1.
random_pibble_init(Y)matrix (D x N) of counts
(D-1) x N matrix
Notation: N is number of samples and
D is number of multinomial categories
Y <- matrix(sample(1:100, 100), 10, 10)
random_pibble_init(Y)
#> [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 0.23335018 0.52313414 0.9289976 0.2591024 -2.01033021 0.36550120
#> [2,] -1.26390928 0.44845581 0.1267756 1.1749439 0.06366321 0.24342540
#> [3,] -0.35249827 -0.78047815 1.8215898 0.4483661 0.81638220 0.04101842
#> [4,] 0.42293861 0.17502914 1.6258030 -0.7859999 0.73859223 0.27999364
#> [5,] -0.63147246 0.07823502 0.3807474 1.1876572 0.46302673 -0.45210105
#> [6,] -0.23665704 -1.66139024 1.4106729 -0.4500333 1.04072459 -0.73501844
#> [7,] -0.06314497 0.54376563 1.7128631 0.4044740 -1.85861702 0.31746679
#> [8,] -1.48048188 -0.10328418 0.6038343 0.6994952 1.00550971 0.31520781
#> [9,] 0.29243179 -0.21771396 1.9036338 0.6247671 -1.50111884 0.20376928
#> [,7] [,8] [,9] [,10]
#> [1,] 0.2383502 0.5678267 -0.7627573 -0.29175856
#> [2,] -3.0406897 1.0224983 -0.1341829 -0.41113968
#> [3,] 0.6363111 -1.4671745 -0.4635436 -0.12853328
#> [4,] -1.1202700 0.3721943 -1.3831264 -0.09188346
#> [5,] 0.7651000 -1.2287189 -1.4413219 -1.35413032
#> [6,] -0.5519723 1.1010085 -0.2975555 -0.81176063
#> [7,] 0.9364162 1.1838267 -1.4963886 0.03638191
#> [8,] -0.4895502 -2.0330977 -0.4169160 -1.89374704
#> [9,] -2.6393401 0.5258394 -0.8236054 -0.87415395