Apply ResNMTF
apply_resnmtf.RdApply ResNMTF to data for a range of biclusters selecting the optimal number, with optional stability analysis
Usage
apply_resnmtf(
data,
init_f = NULL,
init_s = NULL,
init_g = NULL,
k_vec = NULL,
phi = NULL,
xi = NULL,
psi = NULL,
n_iters = NULL,
k_min = 3,
k_max = 8,
distance = "euclidean",
num_repeats = 5,
no_clusts = FALSE,
sample_rate = 0.9,
n_stability = 5,
stability = TRUE,
stab_thres = 0.4,
remove_unstable = TRUE,
use_parallel = TRUE
)Arguments
- data
list of n_v matrices, data to be factorised. If only one view is supplied, can be given as a matrix.
- init_f
list of matrices, initialisation for F matrices
- init_s
list of matrices, initialisation for S matrices
- init_g
list of matrices, initialisation for G matrices
- k_vec
vector of integers, number of clusters to consider in each view, default is NULL
- phi
n_v x n_v matrix, default is NULL, restriction matrices for F
- xi
n_v x n_v matrix, default is NULL, restriction matrices for S
- psi
n_v x n_v matrix, default is NULL, restriction matrices for G
- n_iters
integer, default is NULL, number of iterations to run for, otherwise will run until convergence
- k_min
positive integer, default is 3, smallest value of k to be considered initially,
- k_max
positive integer, default is 6, largest value of k to be considered initially,
- distance
string, default is "euclidean", distance metric to use within the bisilhouette score
- num_repeats
integer, default is 5, number of repeats to use within stability analysis
- no_clusts
boolean, default is FALSE, whether to return only the factorisation or not,
- sample_rate
numeric, default is 0.9, proportion of data to sample for stability analysis,
- n_stability
integer, default is 5, number of times to repeat stability analysis,
- stability
boolean, default is TRUE, whether to perform stability analysis or not,
- stab_thres
numeric, default is 0.4, threshold for stability analysis,
- remove_unstable
boolean, default is TRUE, whether to remove unstable clusters or not
- use_parallel
boolean, default is TRUE, wheather to use parallelisation, not applicable on Windows or linux machines
Value
list of results from ResNMTF, containing the following: - output_f: list of matrices, F matrices - output_s: list of matrices, S matrices - output_g: list of matrices, G matrices - Error: numeric, mean error - All_Error: numeric, all errors - bisil: numeric, bisilhouette score - row_clusters: list of matrices, row clusters - col_clusters: list of matrices, column clusters - lambda: list of vectors, lambda vectors - mu: list of vectors, mu vectors
Examples
row_clusters <- cbind(
rbinom(100, 1, 0.5),
rbinom(100, 1, 0.5),
rbinom(100, 1, 0.5)
)
col_clusters <- cbind(
rbinom(50, 1, 0.4),
rbinom(50, 1, 0.4),
rbinom(50, 1, 0.4)
)
n_col <- 50
data <- list(
row_clusters %*% diag(c(5, 5, 5)) %*% t(col_clusters) +
abs(matrix(rnorm(100 * n_col), 100, n_col)),
row_clusters %*% diag(c(5, 5, 5)) %*% t(col_clusters) +
abs(0.01 * matrix(rnorm(100 * n_col), 100, n_col))
)
apply_resnmtf(data, k_max = 4)
#> $output_f
#> $output_f[[1]]
#> [,1] [,2] [,3]
#> [1,] 1.146132e-03 2.125154e-02 3.446478e-03
#> [2,] 1.494577e-03 1.471902e-03 8.276863e-03
#> [3,] 1.086306e-03 1.975034e-03 8.162363e-03
#> [4,] 1.549786e-02 1.193909e-06 1.731855e-02
#> [5,] 1.697182e-02 1.344827e-03 2.599818e-03
#> [6,] 1.693614e-02 3.461655e-09 6.520452e-03
#> [7,] 1.545141e-02 2.175745e-02 3.248935e-03
#> [8,] 1.579234e-02 2.046717e-02 1.016246e-02
#> [9,] 1.759394e-02 2.027217e-02 1.261481e-03
#> [10,] 1.513659e-02 8.629255e-04 1.607522e-02
#> [11,] 5.686309e-12 2.296943e-08 1.479918e-02
#> [12,] 1.559248e-02 8.888988e-04 1.363640e-02
#> [13,] 1.700079e-02 1.606283e-16 6.139761e-03
#> [14,] 1.613030e-02 5.817570e-04 1.521746e-02
#> [15,] 9.007516e-04 1.838288e-04 1.718925e-02
#> [16,] 1.639320e-02 2.375322e-03 1.261524e-02
#> [17,] 1.576605e-02 4.907717e-06 1.489967e-02
#> [18,] 1.600299e-02 2.172142e-02 8.368387e-03
#> [19,] 1.748153e-02 2.449653e-10 2.767804e-03
#> [20,] 1.643250e-02 1.963616e-02 1.687285e-18
#> [21,] 1.602135e-03 2.162133e-02 2.475514e-03
#> [22,] 1.565229e-02 2.169079e-04 1.555762e-02
#> [23,] 1.545871e-02 1.978517e-02 1.272948e-02
#> [24,] 9.739603e-04 2.219722e-02 1.097805e-02
#> [25,] 7.708661e-04 1.478171e-03 9.057889e-03
#> [26,] 1.572254e-02 2.060945e-02 1.184627e-02
#> [27,] 9.352980e-04 2.225354e-02 1.554074e-02
#> [28,] 1.799697e-04 2.333593e-02 1.406781e-02
#> [29,] 5.564293e-06 3.124796e-03 1.579150e-02
#> [30,] 1.671935e-02 2.291924e-05 4.652841e-03
#> [31,] 1.592342e-02 2.559325e-04 1.360350e-02
#> [32,] 1.679603e-02 2.169928e-02 1.033253e-08
#> [33,] 1.684626e-02 3.802913e-14 6.030135e-03
#> [34,] 1.647155e-02 1.427568e-07 1.392716e-02
#> [35,] 1.582404e-02 2.039867e-02 8.988098e-03
#> [36,] 1.247090e-03 2.134164e-02 5.787113e-03
#> [37,] 2.646271e-04 4.843412e-04 1.979785e-02
#> [38,] 1.643928e-02 9.804374e-04 1.552711e-02
#> [39,] 1.114498e-03 2.103670e-02 1.592078e-02
#> [40,] 1.671633e-02 4.072043e-06 7.665812e-03
#> [41,] 1.516298e-02 2.392420e-02 7.802638e-03
#> [42,] 7.562537e-04 2.143550e-02 3.290563e-03
#> [43,] 1.570789e-02 5.433597e-04 1.354075e-02
#> [44,] 1.385210e-06 2.177213e-02 1.527620e-02
#> [45,] 1.685974e-02 2.200569e-02 1.001392e-02
#> [46,] 9.883709e-04 2.241310e-02 1.579524e-02
#> [47,] 1.587662e-02 2.141681e-02 1.178243e-02
#> [48,] 1.705574e-02 1.820153e-08 3.786976e-03
#> [49,] 1.534640e-02 2.834214e-06 1.491934e-02
#> [50,] 2.158754e-03 1.787409e-03 6.731478e-03
#> [51,] 1.600238e-02 3.171178e-06 1.642579e-02
#> [52,] 7.370847e-04 2.230633e-02 1.180442e-02
#> [53,] 1.918338e-03 6.253288e-05 6.179562e-03
#> [54,] 5.691817e-04 2.190720e-02 1.480326e-02
#> [55,] 1.655629e-02 4.321510e-11 5.259762e-03
#> [56,] 1.156767e-03 2.190487e-02 3.152891e-03
#> [57,] 1.397481e-03 5.443193e-04 1.824334e-02
#> [58,] 1.728790e-02 7.906696e-10 3.574575e-03
#> [59,] 1.704954e-02 2.055244e-02 2.166876e-03
#> [60,] 1.694397e-02 1.318672e-04 1.765099e-02
#> [61,] 1.564871e-02 2.040157e-02 1.166557e-02
#> [62,] 1.628923e-02 1.939123e-04 1.765287e-02
#> [63,] 1.564407e-02 2.064973e-02 1.164028e-02
#> [64,] 1.561675e-02 4.624695e-04 1.601846e-02
#> [65,] 1.644149e-02 2.188809e-02 1.334037e-03
#> [66,] 1.027672e-03 2.356273e-02 3.226703e-03
#> [67,] 1.191844e-03 2.219856e-02 5.031804e-03
#> [68,] 1.637515e-02 3.230965e-04 1.235099e-02
#> [69,] 1.505852e-02 8.312565e-06 1.815438e-02
#> [70,] 4.626371e-06 3.573782e-03 1.481798e-02
#> [71,] 1.354800e-03 1.282430e-04 1.032759e-02
#> [72,] 1.636543e-02 9.352979e-04 1.333794e-02
#> [73,] 6.886749e-04 7.482930e-04 8.669670e-03
#> [74,] 1.551049e-02 1.335090e-04 1.599369e-02
#> [75,] 1.627750e-02 1.371450e-03 1.505771e-02
#> [76,] 1.317933e-03 2.158456e-02 3.434449e-03
#> [77,] 3.436442e-05 2.141154e-02 1.559901e-02
#> [78,] 1.619947e-02 7.954179e-04 1.383430e-02
#> [79,] 1.694377e-02 1.997524e-02 2.331243e-03
#> [80,] 1.271546e-05 2.375112e-02 1.271376e-02
#> [81,] 1.725725e-02 2.443872e-06 3.433459e-03
#> [82,] 9.936427e-04 1.225778e-03 6.649061e-03
#> [83,] 1.672299e-02 1.844714e-07 1.576147e-02
#> [84,] 9.928089e-04 2.157956e-02 5.630948e-03
#> [85,] 1.112770e-03 1.452445e-03 1.849904e-02
#> [86,] 7.482358e-04 1.840823e-04 1.873646e-02
#> [87,] 1.582706e-02 2.055708e-02 1.246482e-02
#> [88,] 1.289086e-03 1.059155e-03 1.419822e-02
#> [89,] 1.636957e-02 2.148396e-02 1.077442e-02
#> [90,] 1.788996e-03 1.743248e-09 1.048216e-02
#> [91,] 2.108219e-03 2.054576e-02 4.538100e-03
#> [92,] 1.663366e-02 2.055472e-02 1.029204e-07
#> [93,] 1.672303e-02 1.951328e-02 1.256936e-02
#> [94,] 1.479148e-03 3.910966e-04 8.672237e-03
#> [95,] 1.774034e-02 2.064779e-02 1.711468e-04
#> [96,] 1.606041e-02 2.231411e-02 4.530070e-12
#> [97,] 2.581646e-04 2.505321e-03 1.413485e-02
#> [98,] 1.691027e-02 4.591886e-06 3.587380e-03
#> [99,] 1.846260e-05 2.358267e-02 1.165122e-02
#> [100,] 1.695811e-02 1.994208e-02 1.115542e-06
#>
#> $output_f[[2]]
#> [,1] [,2] [,3]
#> [1,] 1.066382e-11 2.152188e-02 5.719293e-03
#> [2,] 3.896436e-32 5.406195e-50 7.256978e-03
#> [3,] 6.467403e-26 3.266737e-44 9.219032e-03
#> [4,] 1.689855e-02 4.647960e-04 1.302188e-02
#> [5,] 1.621653e-02 2.927229e-20 6.685743e-03
#> [6,] 1.708249e-02 7.246450e-15 2.975970e-03
#> [7,] 1.687921e-02 2.165335e-02 6.738200e-04
#> [8,] 1.706953e-02 2.249995e-02 1.078814e-02
#> [9,] 1.686100e-02 2.182643e-02 3.329060e-10
#> [10,] 1.680070e-02 1.095467e-09 1.780509e-02
#> [11,] 3.082576e-28 8.765831e-33 9.140822e-03
#> [12,] 1.667228e-02 6.946291e-07 1.557025e-02
#> [13,] 1.705111e-02 1.499403e-17 2.578254e-03
#> [14,] 1.688824e-02 3.087461e-06 1.543597e-02
#> [15,] 1.419428e-06 2.520073e-04 1.684285e-02
#> [16,] 1.693689e-02 1.991346e-05 1.478100e-02
#> [17,] 1.708421e-02 6.770241e-05 1.309190e-02
#> [18,] 1.714985e-02 2.251825e-02 1.238486e-02
#> [19,] 1.686461e-02 5.735703e-16 1.871804e-03
#> [20,] 1.689353e-02 2.170049e-02 1.827692e-03
#> [21,] 4.125243e-10 2.136819e-02 6.365035e-03
#> [22,] 1.717345e-02 5.185808e-05 1.301561e-02
#> [23,] 1.724796e-02 2.252118e-02 1.042137e-02
#> [24,] 6.883410e-10 2.191481e-02 1.605081e-02
#> [25,] 1.403918e-26 1.041892e-46 9.434441e-03
#> [26,] 1.739861e-02 2.272586e-02 1.083761e-02
#> [27,] 1.244035e-04 2.253468e-02 1.386825e-02
#> [28,] 1.314239e-04 2.252017e-02 1.182241e-02
#> [29,] 2.149552e-13 5.707512e-10 2.076117e-02
#> [30,] 1.651511e-02 1.759375e-17 2.828694e-03
#> [31,] 1.666693e-02 2.025264e-08 1.679992e-02
#> [32,] 1.660824e-02 2.218381e-02 1.517561e-03
#> [33,] 1.662875e-02 4.554685e-18 4.381565e-03
#> [34,] 1.712051e-02 9.349792e-05 1.233346e-02
#> [35,] 1.666861e-02 2.264805e-02 1.246413e-02
#> [36,] 2.030739e-04 2.191824e-02 2.050912e-03
#> [37,] 1.226013e-07 2.609510e-04 1.500205e-02
#> [38,] 1.696424e-02 1.754729e-08 1.570056e-02
#> [39,] 3.324162e-05 2.206778e-02 1.718405e-02
#> [40,] 1.694763e-02 1.120731e-19 2.707949e-03
#> [41,] 1.720126e-02 2.253840e-02 1.055948e-02
#> [42,] 1.882622e-07 2.167748e-02 2.746417e-03
#> [43,] 1.719116e-02 2.227907e-08 1.467926e-02
#> [44,] 3.216764e-05 2.251221e-02 1.306497e-02
#> [45,] 1.698623e-02 2.257283e-02 1.279673e-02
#> [46,] 1.036281e-05 2.225538e-02 1.768942e-02
#> [47,] 1.695928e-02 2.292975e-02 1.050338e-02
#> [48,] 1.673959e-02 1.027779e-14 2.787490e-03
#> [49,] 1.714845e-02 1.737990e-05 1.314922e-02
#> [50,] 2.051741e-31 1.845291e-47 1.132996e-02
#> [51,] 1.702241e-02 5.272824e-06 1.583915e-02
#> [52,] 8.111566e-08 2.240939e-02 1.483460e-02
#> [53,] 5.582734e-26 5.319365e-44 8.328600e-03
#> [54,] 4.353283e-06 2.192807e-02 1.772499e-02
#> [55,] 1.682805e-02 2.214541e-21 6.973514e-03
#> [56,] 1.593701e-05 2.167142e-02 3.937639e-03
#> [57,] 1.058589e-11 8.960428e-06 1.847774e-02
#> [58,] 1.693186e-02 3.343237e-18 3.946319e-03
#> [59,] 1.684225e-02 2.164573e-02 1.573714e-03
#> [60,] 1.705507e-02 5.196685e-05 1.511247e-02
#> [61,] 1.690208e-02 2.275078e-02 1.049189e-02
#> [62,] 1.723174e-02 4.287321e-04 1.200355e-02
#> [63,] 1.709380e-02 2.261027e-02 1.028308e-02
#> [64,] 1.715402e-02 2.380239e-04 1.304869e-02
#> [65,] 1.690400e-02 2.194519e-02 3.404324e-09
#> [66,] 1.310916e-11 2.187918e-02 3.236713e-03
#> [67,] 8.230819e-07 2.179137e-02 2.301576e-03
#> [68,] 1.703748e-02 2.720310e-05 1.323379e-02
#> [69,] 1.689591e-02 2.685035e-09 1.817939e-02
#> [70,] 1.950545e-07 3.708162e-04 1.846444e-02
#> [71,] 3.542517e-24 3.068769e-44 7.030013e-03
#> [72,] 1.675707e-02 7.555313e-09 1.709217e-02
#> [73,] 2.094764e-19 1.183969e-40 8.212152e-03
#> [74,] 1.710309e-02 5.813144e-06 1.580752e-02
#> [75,] 1.652180e-02 6.792385e-05 1.555447e-02
#> [76,] 1.769286e-08 2.161001e-02 2.688399e-03
#> [77,] 4.958370e-06 2.238136e-02 1.607248e-02
#> [78,] 1.721007e-02 7.345880e-05 1.410898e-02
#> [79,] 1.706351e-02 2.225526e-02 4.109163e-05
#> [80,] 1.152049e-04 2.244686e-02 1.435252e-02
#> [81,] 1.680966e-02 3.640237e-17 6.071543e-03
#> [82,] 3.217921e-38 1.217219e-38 6.501348e-03
#> [83,] 1.666270e-02 5.167578e-08 1.551709e-02
#> [84,] 1.016220e-08 2.182928e-02 3.162712e-03
#> [85,] 8.562023e-13 1.652219e-07 1.987658e-02
#> [86,] 1.405846e-09 5.989132e-09 2.056915e-02
#> [87,] 1.687890e-02 2.261199e-02 1.130417e-02
#> [88,] 8.470170e-08 1.100343e-07 1.820613e-02
#> [89,] 1.725392e-02 2.273330e-02 1.121514e-02
#> [90,] 5.134125e-20 2.297553e-42 5.860519e-03
#> [91,] 3.384580e-12 2.169930e-02 5.089846e-03
#> [92,] 1.656698e-02 2.191973e-02 2.150411e-08
#> [93,] 1.705505e-02 2.274331e-02 9.976933e-03
#> [94,] 8.143140e-34 3.545823e-49 6.660134e-03
#> [95,] 1.700288e-02 2.202980e-02 1.681733e-03
#> [96,] 1.716199e-02 2.177709e-02 7.287497e-04
#> [97,] 9.517547e-15 3.670752e-11 1.991467e-02
#> [98,] 1.687399e-02 2.057507e-16 1.848640e-03
#> [99,] 1.544589e-06 2.252150e-02 1.433799e-02
#> [100,] 1.698536e-02 2.169016e-02 7.182639e-11
#>
#>
#> $output_s
#> $output_s[[1]]
#> [,1] [,2] [,3]
#> [1,] 18.3692874 0.9744228 0.2634945
#> [2,] 0.2210613 12.2584154 1.4868896
#> [3,] 1.3404007 0.1047910 14.9253031
#>
#> $output_s[[2]]
#> [,1] [,2] [,3]
#> [1,] 19.61147532 0.03951771 0.07682065
#> [2,] 0.02495431 13.74997853 0.74173834
#> [3,] 0.16063438 0.01172958 15.59362578
#>
#>
#> $output_g
#> $output_g[[1]]
#> [,1] [,2] [,3]
#> [1,] 0.0022882489 2.077359e-05 6.154092e-02
#> [2,] 0.0013493536 6.730806e-02 3.164189e-03
#> [3,] 0.0113529086 1.930352e-04 4.140648e-02
#> [4,] 0.0465225643 3.096814e-05 4.620099e-03
#> [5,] 0.0116535229 1.057356e-02 3.336954e-02
#> [6,] 0.0158950220 1.545848e-02 2.426684e-02
#> [7,] 0.0286522265 3.272271e-02 6.982948e-06
#> [8,] 0.0473833794 1.436942e-03 2.086642e-03
#> [9,] 0.0001148794 6.864377e-02 3.907257e-03
#> [10,] 0.0006378225 3.242000e-02 3.601419e-02
#> [11,] 0.0121715454 7.651471e-03 3.386739e-02
#> [12,] 0.0285325226 3.335062e-02 1.615700e-05
#> [13,] 0.0088272185 1.275963e-02 3.597349e-02
#> [14,] 0.0122828597 3.480704e-03 4.030611e-02
#> [15,] 0.0292062156 3.196525e-02 2.235244e-05
#> [16,] 0.0474869894 5.462109e-04 2.776500e-03
#> [17,] 0.0195672620 2.118975e-02 2.192409e-02
#> [18,] 0.0273141199 4.746277e-05 3.023805e-02
#> [19,] 0.0483854831 2.112148e-03 1.478273e-04
#> [20,] 0.0012054735 6.510828e-02 5.840777e-03
#> [21,] 0.0006080423 6.748355e-02 4.663615e-03
#> [22,] 0.0284261569 3.304626e-02 3.327578e-06
#> [23,] 0.0271738232 1.588802e-04 3.012462e-02
#> [24,] 0.0088374445 5.398816e-03 4.264271e-02
#> [25,] 0.0291089314 3.212808e-02 1.140103e-05
#> [26,] 0.0021452218 3.270071e-02 3.415385e-02
#> [27,] 0.0284494146 2.563818e-05 2.864881e-02
#> [28,] 0.0001490632 6.540920e-02 6.658558e-03
#> [29,] 0.0492614289 2.426334e-04 2.008813e-04
#> [30,] 0.0490942955 2.073489e-03 3.332922e-07
#> [31,] 0.0022965605 2.232243e-06 6.223409e-02
#> [32,] 0.0013795854 3.209749e-02 3.560756e-02
#> [33,] 0.0009220423 3.286387e-02 3.521620e-02
#> [34,] 0.0270661088 6.597188e-05 3.087408e-02
#> [35,] 0.0136870093 7.621683e-03 3.089579e-02
#> [36,] 0.0200872622 2.156314e-02 2.107118e-02
#> [37,] 0.0193910154 2.112095e-02 2.188921e-02
#> [38,] 0.0012642287 3.276007e-02 3.487705e-02
#> [39,] 0.0074461051 1.600413e-02 3.456533e-02
#> [40,] 0.0201710767 7.896303e-03 2.481991e-02
#> [41,] 0.0494115516 2.292046e-04 1.784515e-04
#> [42,] 0.0505358961 7.508739e-06 3.525672e-06
#> [43,] 0.0280416453 3.285114e-02 1.446137e-04
#> [44,] 0.0131057577 1.170599e-02 3.285133e-02
#> [45,] 0.0286333193 3.148950e-02 5.277385e-04
#> [46,] 0.0274035057 4.162717e-05 3.026893e-02
#> [47,] 0.0292984457 3.130555e-02 1.592975e-04
#> [48,] 0.0061431165 9.267888e-03 4.011768e-02
#> [49,] 0.0011148914 3.358288e-02 3.486569e-02
#> [50,] 0.0285174361 3.183577e-02 2.283587e-04
#>
#> $output_g[[2]]
#> [,1] [,2] [,3]
#> [1,] 4.192051e-03 9.760293e-07 6.340938e-02
#> [2,] 2.345606e-05 7.263476e-02 1.391442e-05
#> [3,] 6.259943e-04 8.602734e-03 4.743689e-02
#> [4,] 5.070331e-02 3.030264e-08 1.317108e-07
#> [5,] 9.217903e-03 6.600997e-03 4.041727e-02
#> [6,] 8.777465e-03 6.673164e-03 3.712560e-02
#> [7,] 2.865568e-02 3.137777e-02 1.999587e-05
#> [8,] 5.069428e-02 3.192858e-08 1.393313e-07
#> [9,] 2.832129e-05 7.258104e-02 1.690126e-05
#> [10,] 2.321181e-03 3.235929e-02 3.496162e-02
#> [11,] 1.471548e-02 1.208792e-02 2.682041e-02
#> [12,] 2.864796e-02 3.138500e-02 2.002157e-05
#> [13,] 5.430808e-03 1.428517e-02 3.706767e-02
#> [14,] 1.057582e-02 1.134165e-02 3.207035e-02
#> [15,] 2.865148e-02 3.138610e-02 1.966693e-05
#> [16,] 5.069171e-02 3.298182e-08 1.509070e-07
#> [17,] 2.022583e-02 2.036737e-02 2.191810e-02
#> [18,] 2.818274e-02 8.709082e-06 3.059106e-02
#> [19,] 5.069627e-02 3.393538e-08 1.401348e-07
#> [20,] 2.509783e-05 7.264579e-02 1.312255e-05
#> [21,] 2.900190e-05 7.259437e-02 1.532232e-05
#> [22,] 2.864841e-02 3.138855e-02 1.994187e-05
#> [23,] 2.817093e-02 8.995646e-06 3.059710e-02
#> [24,] 9.736137e-03 6.500607e-03 3.869169e-02
#> [25,] 2.865659e-02 3.137576e-02 2.038754e-05
#> [26,] 2.317995e-03 3.234248e-02 3.498332e-02
#> [27,] 2.817068e-02 8.765784e-06 3.060049e-02
#> [28,] 2.697480e-05 7.261558e-02 1.401716e-05
#> [29,] 5.068987e-02 3.516491e-08 1.475041e-07
#> [30,] 5.069917e-02 3.341827e-08 1.420113e-07
#> [31,] 4.188054e-03 8.803024e-07 6.342487e-02
#> [32,] 2.304903e-03 3.235741e-02 3.498855e-02
#> [33,] 2.309782e-03 3.235088e-02 3.498492e-02
#> [34,] 2.817259e-02 8.620134e-06 3.059541e-02
#> [35,] 1.215551e-02 3.166535e-03 3.646578e-02
#> [36,] 2.023572e-02 2.037680e-02 2.189578e-02
#> [37,] 2.023089e-02 2.037066e-02 2.190876e-02
#> [38,] 2.307022e-03 3.235556e-02 3.498332e-02
#> [39,] 1.159246e-02 1.144904e-02 3.368562e-02
#> [40,] 1.254191e-02 6.830605e-03 3.615353e-02
#> [41,] 5.069691e-02 3.346738e-08 1.354883e-07
#> [42,] 5.069430e-02 3.873446e-08 1.404800e-07
#> [43,] 2.864699e-02 3.137972e-02 2.075281e-05
#> [44,] 7.738229e-03 3.301371e-03 4.285935e-02
#> [45,] 2.865750e-02 3.137654e-02 1.941887e-05
#> [46,] 2.816812e-02 9.007440e-06 3.059999e-02
#> [47,] 2.864856e-02 3.138919e-02 2.003699e-05
#> [48,] 9.515409e-03 8.394347e-03 3.551017e-02
#> [49,] 2.314473e-03 3.233128e-02 3.499760e-02
#> [50,] 2.865211e-02 3.137774e-02 2.074029e-05
#>
#>
#> $Error
#> [1] 0.1091528
#>
#> $All_Error
#> [1] 0.2562982 0.2446796 0.2392952 0.2383506 0.2375588 0.2361998 0.2335120
#> [8] 0.2286205 0.2225245 0.2170010 0.2123091 0.2081617 0.2042605 0.2004325
#> [15] 0.1966182 0.1928139 0.1890153 0.1852003 0.1813527 0.1774878 0.1736503
#> [22] 0.1698906 0.1662405 0.1627087 0.1592952 0.1560110 0.1528875 0.1499672
#> [29] 0.1472833 0.1448434 0.1426262 0.1405914 0.1386926 0.1368879 0.1351461
#> [36] 0.1334477 0.1317844 0.1301568 0.1285728 0.1270445 0.1255859 0.1242108
#> [43] 0.1229306 0.1217534 0.1206828 0.1197182 0.1188553 0.1180872 0.1174050
#> [50] 0.1167994 0.1162607 0.1157800 0.1153492 0.1149614 0.1146106 0.1142919
#> [57] 0.1140009 0.1137345 0.1134896 0.1132638 0.1130552 0.1128619 0.1126824
#> [64] 0.1125154 0.1123597 0.1122143 0.1120783 0.1119509 0.1118313 0.1117189
#> [71] 0.1116132 0.1115136 0.1114197 0.1113311 0.1112474 0.1111683 0.1110934
#> [78] 0.1110225 0.1109554 0.1108917 0.1108313 0.1107740 0.1107196 0.1106678
#> [85] 0.1106185 0.1105717 0.1105270 0.1104844 0.1104437 0.1104048 0.1103677
#> [92] 0.1103321 0.1102981 0.1102655 0.1102342 0.1102041 0.1101753 0.1101475
#> [99] 0.1101208 0.1100950 0.1100702 0.1100462 0.1100230 0.1100005 0.1099787
#> [106] 0.1099575 0.1099369 0.1099168 0.1098972 0.1098780 0.1098593 0.1098409
#> [113] 0.1098230 0.1098054 0.1097881 0.1097713 0.1097548 0.1097388 0.1097231
#> [120] 0.1097079 0.1096931 0.1096787 0.1096648 0.1096513 0.1096383 0.1096257
#> [127] 0.1096135 0.1096018 0.1095904 0.1095794 0.1095688 0.1095585 0.1095485
#> [134] 0.1095388 0.1095294 0.1095202 0.1095113 0.1095025 0.1094940 0.1094857
#> [141] 0.1094776 0.1094696 0.1094618 0.1094541 0.1094466 0.1094393 0.1094322
#> [148] 0.1094253 0.1094185 0.1094120 0.1094056 0.1093995 0.1093936 0.1093878
#> [155] 0.1093822 0.1093768 0.1093716 0.1093665 0.1093615 0.1093567 0.1093519
#> [162] 0.1093473 0.1093428 0.1093384 0.1093341 0.1093299 0.1093257 0.1093216
#> [169] 0.1093175 0.1093135 0.1093095 0.1093056 0.1093017 0.1092979 0.1092941
#> [176] 0.1092903 0.1092865 0.1092828 0.1092790 0.1092753 0.1092716 0.1092679
#> [183] 0.1092642 0.1092605 0.1092567 0.1092530 0.1092494 0.1092458 0.1092423
#> [190] 0.1092390 0.1092357 0.1092327 0.1092297 0.1092269 0.1092243 0.1092217
#> [197] 0.1092192 0.1092168 0.1092145 0.1092122 0.1092100 0.1092079 0.1092058
#> [204] 0.1092037 0.1092017 0.1091997 0.1091977 0.1091958 0.1091939 0.1091920
#> [211] 0.1091902 0.1091884 0.1091867 0.1091849 0.1091832 0.1091816 0.1091799
#> [218] 0.1091783 0.1091767 0.1091751 0.1091736 0.1091721 0.1091706 0.1091691
#> [225] 0.1091676 0.1091661 0.1091647 0.1091633 0.1091619 0.1091606 0.1091593
#> [232] 0.1091580 0.1091567 0.1091555 0.1091543 0.1091532 0.1091521 0.1091510
#> [239] 0.1091500 0.1091490 0.1091480
#>
#> $bisil
#> [1] 0.1954041
#>
#> $row_clusters
#> $row_clusters[[1]]
#> [,1] [,2] [,3]
#> [1,] 0 1 0
#> [2,] 0 0 0
#> [3,] 0 0 0
#> [4,] 1 0 1
#> [5,] 1 0 0
#> [6,] 1 0 0
#> [7,] 1 1 0
#> [8,] 1 1 1
#> [9,] 1 1 0
#> [10,] 1 0 1
#> [11,] 0 0 1
#> [12,] 1 0 1
#> [13,] 1 0 0
#> [14,] 1 0 1
#> [15,] 0 0 1
#> [16,] 1 0 1
#> [17,] 1 0 1
#> [18,] 1 1 0
#> [19,] 1 0 0
#> [20,] 1 1 0
#> [21,] 0 1 0
#> [22,] 1 0 1
#> [23,] 1 1 1
#> [24,] 0 1 1
#> [25,] 0 0 0
#> [26,] 1 1 1
#> [27,] 0 1 1
#> [28,] 0 1 1
#> [29,] 0 0 1
#> [30,] 1 0 0
#> [31,] 1 0 1
#> [32,] 1 1 0
#> [33,] 1 0 0
#> [34,] 1 0 1
#> [35,] 1 1 0
#> [36,] 0 1 0
#> [37,] 0 0 1
#> [38,] 1 0 1
#> [39,] 0 1 1
#> [40,] 1 0 0
#> [41,] 1 1 0
#> [42,] 0 1 0
#> [43,] 1 0 1
#> [44,] 0 1 1
#> [45,] 1 1 1
#> [46,] 0 1 1
#> [47,] 1 1 1
#> [48,] 1 0 0
#> [49,] 1 0 1
#> [50,] 0 0 0
#> [51,] 1 0 1
#> [52,] 0 1 1
#> [53,] 0 0 0
#> [54,] 0 1 1
#> [55,] 1 0 0
#> [56,] 0 1 0
#> [57,] 0 0 1
#> [58,] 1 0 0
#> [59,] 1 1 0
#> [60,] 1 0 1
#> [61,] 1 1 1
#> [62,] 1 0 1
#> [63,] 1 1 1
#> [64,] 1 0 1
#> [65,] 1 1 0
#> [66,] 0 1 0
#> [67,] 0 1 0
#> [68,] 1 0 1
#> [69,] 1 0 1
#> [70,] 0 0 1
#> [71,] 0 0 1
#> [72,] 1 0 1
#> [73,] 0 0 0
#> [74,] 1 0 1
#> [75,] 1 0 1
#> [76,] 0 1 0
#> [77,] 0 1 1
#> [78,] 1 0 1
#> [79,] 1 1 0
#> [80,] 0 1 1
#> [81,] 1 0 0
#> [82,] 0 0 0
#> [83,] 1 0 1
#> [84,] 0 1 0
#> [85,] 0 0 1
#> [86,] 0 0 1
#> [87,] 1 1 1
#> [88,] 0 0 1
#> [89,] 1 1 1
#> [90,] 0 0 1
#> [91,] 0 1 0
#> [92,] 1 1 0
#> [93,] 1 1 1
#> [94,] 0 0 0
#> [95,] 1 1 0
#> [96,] 1 1 0
#> [97,] 0 0 1
#> [98,] 1 0 0
#> [99,] 0 1 1
#> [100,] 1 1 0
#>
#> $row_clusters[[2]]
#> [,1] [,2] [,3]
#> [1,] 0 1 0
#> [2,] 0 0 0
#> [3,] 0 0 0
#> [4,] 1 0 1
#> [5,] 1 0 0
#> [6,] 1 0 0
#> [7,] 1 1 0
#> [8,] 1 1 1
#> [9,] 1 1 0
#> [10,] 1 0 1
#> [11,] 0 0 0
#> [12,] 1 0 1
#> [13,] 1 0 0
#> [14,] 1 0 1
#> [15,] 0 0 1
#> [16,] 1 0 1
#> [17,] 1 0 1
#> [18,] 1 1 1
#> [19,] 1 0 0
#> [20,] 1 1 0
#> [21,] 0 1 0
#> [22,] 1 0 1
#> [23,] 1 1 1
#> [24,] 0 1 1
#> [25,] 0 0 0
#> [26,] 1 1 1
#> [27,] 0 1 1
#> [28,] 0 1 1
#> [29,] 0 0 1
#> [30,] 1 0 0
#> [31,] 1 0 1
#> [32,] 1 1 0
#> [33,] 1 0 0
#> [34,] 1 0 1
#> [35,] 1 1 1
#> [36,] 0 1 0
#> [37,] 0 0 1
#> [38,] 1 0 1
#> [39,] 0 1 1
#> [40,] 1 0 0
#> [41,] 1 1 1
#> [42,] 0 1 0
#> [43,] 1 0 1
#> [44,] 0 1 1
#> [45,] 1 1 1
#> [46,] 0 1 1
#> [47,] 1 1 1
#> [48,] 1 0 0
#> [49,] 1 0 1
#> [50,] 0 0 1
#> [51,] 1 0 1
#> [52,] 0 1 1
#> [53,] 0 0 0
#> [54,] 0 1 1
#> [55,] 1 0 0
#> [56,] 0 1 0
#> [57,] 0 0 1
#> [58,] 1 0 0
#> [59,] 1 1 0
#> [60,] 1 0 1
#> [61,] 1 1 1
#> [62,] 1 0 1
#> [63,] 1 1 1
#> [64,] 1 0 1
#> [65,] 1 1 0
#> [66,] 0 1 0
#> [67,] 0 1 0
#> [68,] 1 0 1
#> [69,] 1 0 1
#> [70,] 0 0 1
#> [71,] 0 0 0
#> [72,] 1 0 1
#> [73,] 0 0 0
#> [74,] 1 0 1
#> [75,] 1 0 1
#> [76,] 0 1 0
#> [77,] 0 1 1
#> [78,] 1 0 1
#> [79,] 1 1 0
#> [80,] 0 1 1
#> [81,] 1 0 0
#> [82,] 0 0 0
#> [83,] 1 0 1
#> [84,] 0 1 0
#> [85,] 0 0 1
#> [86,] 0 0 1
#> [87,] 1 1 1
#> [88,] 0 0 1
#> [89,] 1 1 1
#> [90,] 0 0 0
#> [91,] 0 1 0
#> [92,] 1 1 0
#> [93,] 1 1 0
#> [94,] 0 0 0
#> [95,] 1 1 0
#> [96,] 1 1 0
#> [97,] 0 0 1
#> [98,] 1 0 0
#> [99,] 0 1 1
#> [100,] 1 1 0
#>
#>
#> $col_clusters
#> $col_clusters[[1]]
#> [,1] [,2] [,3]
#> [1,] 0 0 1
#> [2,] 0 1 0
#> [3,] 0 0 1
#> [4,] 1 0 0
#> [5,] 0 0 1
#> [6,] 0 0 1
#> [7,] 1 1 0
#> [8,] 1 0 0
#> [9,] 0 1 0
#> [10,] 0 1 1
#> [11,] 0 0 1
#> [12,] 1 1 0
#> [13,] 0 0 1
#> [14,] 0 0 1
#> [15,] 1 1 0
#> [16,] 1 0 0
#> [17,] 0 1 1
#> [18,] 1 0 1
#> [19,] 1 0 0
#> [20,] 0 1 0
#> [21,] 0 1 0
#> [22,] 1 1 0
#> [23,] 1 0 1
#> [24,] 0 0 1
#> [25,] 1 1 0
#> [26,] 0 1 1
#> [27,] 1 0 1
#> [28,] 0 1 0
#> [29,] 1 0 0
#> [30,] 1 0 0
#> [31,] 0 0 1
#> [32,] 0 1 1
#> [33,] 0 1 1
#> [34,] 1 0 1
#> [35,] 0 0 1
#> [36,] 1 1 1
#> [37,] 0 1 1
#> [38,] 0 1 1
#> [39,] 0 0 1
#> [40,] 1 0 1
#> [41,] 1 0 0
#> [42,] 1 0 0
#> [43,] 1 1 0
#> [44,] 0 0 1
#> [45,] 1 1 0
#> [46,] 1 0 1
#> [47,] 1 1 0
#> [48,] 0 0 1
#> [49,] 0 1 1
#> [50,] 1 1 0
#>
#> $col_clusters[[2]]
#> [,1] [,2] [,3]
#> [1,] 0 0 1
#> [2,] 0 1 0
#> [3,] 0 0 1
#> [4,] 1 0 0
#> [5,] 0 0 1
#> [6,] 0 0 1
#> [7,] 1 1 0
#> [8,] 1 0 0
#> [9,] 0 1 0
#> [10,] 0 1 1
#> [11,] 0 0 1
#> [12,] 1 1 0
#> [13,] 0 0 1
#> [14,] 0 0 1
#> [15,] 1 1 0
#> [16,] 1 0 0
#> [17,] 1 1 1
#> [18,] 1 0 1
#> [19,] 1 0 0
#> [20,] 0 1 0
#> [21,] 0 1 0
#> [22,] 1 1 0
#> [23,] 1 0 1
#> [24,] 0 0 1
#> [25,] 1 1 0
#> [26,] 0 1 1
#> [27,] 1 0 1
#> [28,] 0 1 0
#> [29,] 1 0 0
#> [30,] 1 0 0
#> [31,] 0 0 1
#> [32,] 0 1 1
#> [33,] 0 1 1
#> [34,] 1 0 1
#> [35,] 0 0 1
#> [36,] 1 1 1
#> [37,] 1 1 1
#> [38,] 0 1 1
#> [39,] 0 0 1
#> [40,] 0 0 1
#> [41,] 1 0 0
#> [42,] 1 0 0
#> [43,] 1 1 0
#> [44,] 0 0 1
#> [45,] 1 1 0
#> [46,] 1 0 1
#> [47,] 1 1 0
#> [48,] 0 0 1
#> [49,] 0 1 1
#> [50,] 1 1 0
#>
#>
#> $lambda
#> $lambda[[1]]
#> [1] 1.941881e-151 3.393072e-172 3.584933e-170
#>
#> $lambda[[2]]
#> [1] 1.183691e-140 1.922585e-176 1.895918e-186
#>
#>
#> $mu
#> $mu[[1]]
#> [1] 2.216647e-133 1.509655e-173 1.113503e-174
#>
#> $mu[[2]]
#> [1] 2.891488e-132 4.204643e-175 8.811417e-151
#>
#>