EM Algorithm for Mixtures of Logistic Regressions — logisregmixEM • mixtools

Returns EM algorithm output for mixtures of logistic regressions with arbitrarily many components.

Usage

logisregmixEM(y, x, N = NULL, lambda = NULL, beta = NULL, k = 2,
              addintercept = TRUE, epsilon = 1e-08, 
              maxit = 10000, verb = FALSE)

Arguments

y: An n-vector of successes out of N trials.
x: An nxp matrix of predictors. See addintercept below.
N: An n-vector of number of trials for the logistic regression. If NULL, then N is an n-vector of 1s for binary logistic regression.
lambda: Initial value of mixing proportions. Entries should sum to 1. This determines number of components. If NULL, then lambda is random from uniform Dirichlet and number of components is determined by beta.
beta: Initial value of beta parameters. Should be a pxk matrix, where p is the number of columns of x and k is number of components. If NULL, then beta is generated by binning the data into k bins and using glm on the values in each of the bins. If both lambda and beta are NULL, then number of components is determined by k.
k: Number of components. Ignored unless lambda and beta are both NULL.
addintercept: If TRUE, a column of ones is appended to the x matrix before the value of p is calculated.
epsilon: The convergence criterion.
maxit: The maximum number of iterations.
verb: If TRUE, then various updates are printed during each iteration of the algorithm.

Value

logisregmixEM returns a list of class mixEM with items:

x: The predictor values.
y: The response values.
lambda: The final mixing proportions.
beta: The final logistic regression coefficients.
loglik: The final log-likelihood.
posterior: An nxk matrix of posterior probabilities for observations.
all.loglik: A vector of each iteration's log-likelihood.
restarts: The number of times the algorithm restarted due to unacceptable choice of initial values.
ft: A character vector giving the name of the function.

See also

References

McLachlan, G. J. and Peel, D. (2000) Finite Mixture Models, John Wiley and Sons, Inc.

Examples

## EM output for data generated from a 2-component logistic regression model.

set.seed(100)
beta <- matrix(c(1, .5, 2, -.8), 2, 2)
x <- runif(50, 0, 10)
x1 <- cbind(1, x)
xbeta <- x1%*%beta
N <- ceiling(runif(50, 50, 75))
w <- rbinom(50, 1, .3)
y <- w*rbinom(50, size = N, prob = (1/(1+exp(-xbeta[, 1]))))+
              (1-w)*rbinom(50, size = N, prob = 
              (1/(1+exp(-xbeta[, 2]))))
out.1 <- logisregmixEM(y, x, N, verb = TRUE, epsilon = 1e-01)
#> iteration= 1 diff= 558.9581 log-likelihood -266.3327 
#> iteration= 2 diff= 75.25314 log-likelihood -191.0795 
#> iteration= 3 diff= 41.06443 log-likelihood -150.0151 
#> iteration= 4 diff= 17.95687 log-likelihood -132.0583 
#> iteration= 5 diff= 9.104752 log-likelihood -122.9535 
#> iteration= 6 diff= 0.934972 log-likelihood -122.0185 
#> iteration= 7 diff= 0.1560255 log-likelihood -121.8625 
#> iteration= 8 diff= 0.0239556 log-likelihood -121.8385 
#> number of iterations= 8 
out.1
#> $x
#>                 x
#>  [1,] 1 3.0776611
#>  [2,] 1 2.5767250
#>  [3,] 1 5.5232243
#>  [4,] 1 0.5638315
#>  [5,] 1 4.6854928
#>  [6,] 1 4.8377074
#>  [7,] 1 8.1240262
#>  [8,] 1 3.7032054
#>  [9,] 1 5.4655860
#> [10,] 1 1.7026205
#> [11,] 1 6.2499648
#> [12,] 1 8.8216552
#> [13,] 1 2.8035384
#> [14,] 1 3.9848790
#> [15,] 1 7.6255108
#> [16,] 1 6.6902171
#> [17,] 1 2.0461216
#> [18,] 1 3.5752485
#> [19,] 1 3.5947511
#> [20,] 1 6.9029053
#> [21,] 1 5.3581115
#> [22,] 1 7.1080385
#> [23,] 1 5.3834870
#> [24,] 1 7.4897223
#> [25,] 1 4.2010145
#> [26,] 1 1.7142021
#> [27,] 1 7.7030161
#> [28,] 1 8.8195359
#> [29,] 1 5.4909671
#> [30,] 1 2.7772376
#> [31,] 1 4.8830599
#> [32,] 1 9.2850507
#> [33,] 1 3.4869198
#> [34,] 1 9.5415771
#> [35,] 1 6.9527414
#> [36,] 1 8.8945354
#> [37,] 1 1.8040725
#> [38,] 1 6.2939085
#> [39,] 1 9.8956414
#> [40,] 1 1.3028887
#> [41,] 1 3.3066053
#> [42,] 1 8.6512055
#> [43,] 1 7.7758444
#> [44,] 1 8.2730345
#> [45,] 1 6.0332436
#> [46,] 1 4.9123182
#> [47,] 1 7.8035851
#> [48,] 1 8.8422703
#> [49,] 1 2.0771390
#> [50,] 1 3.0708590
#> 
#> $y
#>  [1] 22 33  7 44  8 11 53 52  2 37 60 67 35 14 62  4 59 58 11 66  5  2 10  1 15
#> [26] 49 70 70  5 24  7 65 66  0  1  0 42  5  0 53 27  0  1 60  5 59 63  0 32 25
#> 
#> $lambda
#> [1] 0.6881566 0.3118434
#> 
#> $beta
#>            comp.1    comp.2
#> beta.0  2.0954934 1.2448061
#> beta.1 -0.8112017 0.3980175
#> 
#> $loglik
#> [1] -121.8385
#> 
#> $posterior
#>              comp.1       comp.2
#>  [1,]  1.000000e+00 0.000000e+00
#>  [2,]  1.000000e+00 2.614290e-08
#>  [3,]  1.000000e+00 0.000000e+00
#>  [4,]  5.402273e-01 4.597727e-01
#>  [5,]  1.000000e+00 0.000000e+00
#>  [6,]  1.000000e+00 0.000000e+00
#>  [7,] 7.304589e-102 1.000000e+00
#>  [8,]  6.994855e-23 1.000000e+00
#>  [9,]  1.000000e+00 0.000000e+00
#> [10,]  9.998102e-01 1.897721e-04
#> [11,]  2.402191e-75 1.000000e+00
#> [12,] 1.558874e-147 1.000000e+00
#> [13,]  1.000000e+00 0.000000e+00
#> [14,]  1.000000e+00 0.000000e+00
#> [15,] 1.412169e-110 1.000000e+00
#> [16,]  1.000000e+00 0.000000e+00
#> [17,]  2.049223e-08 1.000000e+00
#> [18,]  3.509595e-24 1.000000e+00
#> [19,]  1.000000e+00 0.000000e+00
#> [20,]  1.134143e-97 1.000000e+00
#> [21,]  1.000000e+00 0.000000e+00
#> [22,]  1.000000e+00 0.000000e+00
#> [23,]  1.000000e+00 0.000000e+00
#> [24,]  1.000000e+00 0.000000e+00
#> [25,]  1.000000e+00 0.000000e+00
#> [26,]  9.748922e-01 2.510784e-02
#> [27,] 6.211936e-123 1.000000e+00
#> [28,] 4.532412e-154 1.000000e+00
#> [29,]  1.000000e+00 0.000000e+00
#> [30,]  1.000000e+00 1.110223e-16
#> [31,]  1.000000e+00 0.000000e+00
#> [32,] 9.883801e-154 1.000000e+00
#> [33,]  1.136275e-23 1.000000e+00
#> [34,]  1.000000e+00 0.000000e+00
#> [35,]  1.000000e+00 0.000000e+00
#> [36,]  1.000000e+00 0.000000e+00
#> [37,]  9.999998e-01 1.654085e-07
#> [38,]  1.000000e+00 0.000000e+00
#> [39,]  1.000000e+00 0.000000e+00
#> [40,]  8.929092e-01 1.070908e-01
#> [41,]  1.000000e+00 0.000000e+00
#> [42,]  1.000000e+00 0.000000e+00
#> [43,]  1.000000e+00 0.000000e+00
#> [44,] 1.193747e-116 1.000000e+00
#> [45,]  1.000000e+00 0.000000e+00
#> [46,]  4.945468e-50 1.000000e+00
#> [47,] 2.866389e-116 1.000000e+00
#> [48,]  1.000000e+00 0.000000e+00
#> [49,]  9.999934e-01 6.605107e-06
#> [50,]  1.000000e+00 0.000000e+00
#> 
#> $all.loglik
#> [1] -825.2908 -266.3327 -191.0795 -150.0151 -132.0583 -122.9535 -122.0185
#> [8] -121.8625 -121.8385
#> 
#> $restarts
#> [1] 0
#> 
#> $ft
#> [1] "logisregmixEM"
#> 
#> attr(,"class")
#> [1] "mixEM"

## EM output for data generated from a 2-component binary logistic regression model.

beta <- matrix(c(-10, .1, 20, -.1), 2, 2)
x <- runif(500, 50, 250)
x1 <- cbind(1, x)
xbeta <- x1%*%beta
w <- rbinom(500, 1, .3)
y <- w*rbinom(500, size = 1, prob = (1/(1+exp(-xbeta[, 1]))))+
              (1-w)*rbinom(500, size = 1, prob = 
              (1/(1+exp(-xbeta[, 2]))))
out.2 <- logisregmixEM(y, x, beta = beta, lambda = c(.3, .7), 
                       verb = TRUE, epsilon = 1e-01)
#> iteration= 1 diff= 1.202696 log-likelihood -216.7515 
#> iteration= 2 diff= 0.1703308 log-likelihood -216.5812 
#> iteration= 3 diff= 0.07258293 log-likelihood -216.5086 
#> number of iterations= 3 
out.2
#> $x
#>                  x
#>   [1,] 1 231.08952
#>   [2,] 1  89.51134
#>   [3,] 1 208.81704
#>   [4,] 1 200.92058
#>   [5,] 1 232.27897
#>   [6,] 1 114.53754
#>   [7,] 1  67.23389
#>   [8,] 1 232.24009
#>   [9,] 1 241.03477
#>  [10,] 1 184.22859
#>  [11,] 1 198.99644
#>  [12,] 1 138.00340
#>  [13,] 1  73.00788
#>  [14,] 1 185.12856
#>  [15,] 1 196.31190
#>  [16,] 1 146.79698
#>  [17,] 1  84.20961
#>  [18,] 1 185.16971
#>  [19,] 1 102.59799
#>  [20,] 1 118.29617
#>  [21,] 1  92.04911
#>  [22,] 1  53.26392
#>  [23,] 1 125.35258
#>  [24,] 1 162.46148
#>  [25,] 1 185.99692
#>  [26,] 1 199.07775
#>  [27,] 1 240.01454
#>  [28,] 1  82.61814
#>  [29,] 1 114.95138
#>  [30,] 1  76.54321
#>  [31,] 1 177.45949
#>  [32,] 1 116.18592
#>  [33,] 1 179.81591
#>  [34,] 1 110.57767
#>  [35,] 1  64.24665
#>  [36,] 1 182.47809
#>  [37,] 1 201.92071
#>  [38,] 1 160.67203
#>  [39,] 1 157.85442
#>  [40,] 1 219.91846
#>  [41,] 1 180.64519
#>  [42,] 1 240.17715
#>  [43,] 1 173.44461
#>  [44,] 1 148.56813
#>  [45,] 1 245.20131
#>  [46,] 1 148.06904
#>  [47,] 1 181.03446
#>  [48,] 1 169.76036
#>  [49,] 1 239.51380
#>  [50,] 1 123.60230
#>  [51,] 1 225.63740
#>  [52,] 1 140.97501
#>  [53,] 1 149.29340
#>  [54,] 1 142.12312
#>  [55,] 1 173.58164
#>  [56,] 1 170.82870
#>  [57,] 1 207.17592
#>  [58,] 1 161.05369
#>  [59,] 1 203.79567
#>  [60,] 1 130.85713
#>  [61,] 1 152.14396
#>  [62,] 1 154.70729
#>  [63,] 1 248.55984
#>  [64,] 1 135.92948
#>  [65,] 1 249.20225
#>  [66,] 1 207.32005
#>  [67,] 1 153.18213
#>  [68,] 1 150.53759
#>  [69,] 1 232.32750
#>  [70,] 1 102.88318
#>  [71,] 1  84.77137
#>  [72,] 1 130.06625
#>  [73,] 1 157.67148
#>  [74,] 1  98.99287
#>  [75,] 1 125.17019
#>  [76,] 1 166.05071
#>  [77,] 1  91.79106
#>  [78,] 1 210.26600
#>  [79,] 1 177.76048
#>  [80,] 1 197.26615
#>  [81,] 1 137.76248
#>  [82,] 1 165.96248
#>  [83,] 1 101.20880
#>  [84,] 1 142.74365
#>  [85,] 1  83.72297
#>  [86,] 1 172.77891
#>  [87,] 1 241.62052
#>  [88,] 1 145.63895
#>  [89,] 1 200.23187
#>  [90,] 1  54.11664
#>  [91,] 1  84.19381
#>  [92,] 1 177.99330
#>  [93,] 1  82.99570
#>  [94,] 1 120.94456
#>  [95,] 1  87.28529
#>  [96,] 1 229.53123
#>  [97,] 1  97.55677
#>  [98,] 1 246.98870
#>  [99,] 1  54.26615
#> [100,] 1  71.50779
#> [101,] 1  98.96537
#> [102,] 1 194.47248
#> [103,] 1  56.54699
#> [104,] 1 159.87000
#> [105,] 1 186.56174
#> [106,] 1 110.04818
#> [107,] 1 127.75489
#> [108,] 1 196.48923
#> [109,] 1 242.49928
#> [110,] 1 202.11923
#> [111,] 1 166.33463
#> [112,] 1 142.57460
#> [113,] 1 121.26192
#> [114,] 1 126.78436
#> [115,] 1  91.15621
#> [116,] 1  77.75607
#> [117,] 1 127.81643
#> [118,] 1 103.20924
#> [119,] 1 190.65926
#> [120,] 1 131.57563
#> [121,] 1 103.11284
#> [122,] 1 130.19557
#> [123,] 1  89.46263
#> [124,] 1 215.98634
#> [125,] 1 155.59755
#> [126,] 1 129.02604
#> [127,] 1 164.79331
#> [128,] 1 244.19441
#> [129,] 1 180.02997
#> [130,] 1 116.72023
#> [131,] 1 116.28949
#> [132,] 1 238.48698
#> [133,] 1 126.22250
#> [134,] 1 162.86478
#> [135,] 1 152.30314
#> [136,] 1  77.77211
#> [137,] 1  97.95788
#> [138,] 1 193.60182
#> [139,] 1 109.44476
#> [140,] 1 152.24748
#> [141,] 1 105.54213
#> [142,] 1 122.13139
#> [143,] 1 137.50557
#> [144,] 1 210.61335
#> [145,] 1 154.12195
#> [146,] 1 189.23041
#> [147,] 1 219.56738
#> [148,] 1 219.14185
#> [149,] 1 128.37515
#> [150,] 1  80.70275
#> [151,] 1 177.88516
#> [152,] 1 107.43420
#> [153,] 1 235.66758
#> [154,] 1  81.12722
#> [155,] 1 242.76833
#> [156,] 1  50.25210
#> [157,] 1 191.50524
#> [158,] 1 176.03752
#> [159,] 1 204.61561
#> [160,] 1 228.52138
#> [161,] 1 152.24082
#> [162,] 1 199.80021
#> [163,] 1 235.27596
#> [164,] 1  68.35070
#> [165,] 1 149.33110
#> [166,] 1  89.50025
#> [167,] 1 248.82658
#> [168,] 1  57.36421
#> [169,] 1  93.51261
#> [170,] 1 228.18723
#> [171,] 1  73.78729
#> [172,] 1 123.80780
#> [173,] 1  82.47529
#> [174,] 1  83.33830
#> [175,] 1 244.50094
#> [176,] 1 212.07995
#> [177,] 1 240.66553
#> [178,] 1 129.98211
#> [179,] 1 220.44946
#> [180,] 1  62.90457
#> [181,] 1 110.50575
#> [182,] 1 148.09457
#> [183,] 1 179.25225
#> [184,] 1 152.12687
#> [185,] 1 209.45185
#> [186,] 1 163.00179
#> [187,] 1 120.70480
#> [188,] 1 181.81999
#> [189,] 1  97.85492
#> [190,] 1 103.04216
#> [191,] 1 153.65377
#> [192,] 1 197.58217
#> [193,] 1 205.92218
#> [194,] 1  72.93888
#> [195,] 1 172.47467
#> [196,] 1 232.18724
#> [197,] 1 176.80429
#> [198,] 1 104.93281
#> [199,] 1 120.56707
#> [200,] 1 184.16587
#> [201,] 1 231.34228
#> [202,] 1 196.04717
#> [203,] 1 233.95340
#> [204,] 1 126.48665
#> [205,] 1 220.82811
#> [206,] 1  60.94682
#> [207,] 1 100.79721
#> [208,] 1 123.42580
#> [209,] 1 122.11408
#> [210,] 1 106.10331
#> [211,] 1 127.73850
#> [212,] 1 119.62689
#> [213,] 1 105.78461
#> [214,] 1 210.21763
#> [215,] 1 249.00277
#> [216,] 1 200.64839
#> [217,] 1 170.66859
#> [218,] 1 168.78964
#> [219,] 1 166.45806
#> [220,] 1  97.73186
#> [221,] 1 140.85688
#> [222,] 1 249.10333
#> [223,] 1  66.54920
#> [224,] 1  60.38120
#> [225,] 1 148.75944
#> [226,] 1  60.79872
#> [227,] 1 240.08971
#> [228,] 1 176.63825
#> [229,] 1 103.98742
#> [230,] 1 249.36259
#> [231,] 1 121.76082
#> [232,] 1 124.35242
#> [233,] 1 116.04528
#> [234,] 1  70.87910
#> [235,] 1 165.98029
#> [236,] 1 116.61789
#> [237,] 1  50.75552
#> [238,] 1 248.91922
#> [239,] 1 123.84697
#> [240,] 1  94.04651
#> [241,] 1 198.63190
#> [242,] 1 111.19146
#> [243,] 1 130.44177
#> [244,] 1 128.71429
#> [245,] 1 138.15129
#> [246,] 1 204.56102
#> [247,] 1  91.91381
#> [248,] 1 199.62454
#> [249,] 1 167.07103
#> [250,] 1 114.88944
#> [251,] 1 125.00949
#> [252,] 1  55.38744
#> [253,] 1 146.66698
#> [254,] 1 244.01609
#> [255,] 1  50.07901
#> [256,] 1  71.14051
#> [257,] 1 137.98864
#> [258,] 1 112.45975
#> [259,] 1 244.26657
#> [260,] 1 167.05377
#> [261,] 1 196.78573
#> [262,] 1 182.70543
#> [263,] 1 194.59690
#> [264,] 1  72.20299
#> [265,] 1  93.71584
#> [266,] 1 174.51326
#> [267,] 1 241.85609
#> [268,] 1 212.46315
#> [269,] 1  54.43257
#> [270,] 1 186.50781
#> [271,] 1 216.15751
#> [272,] 1 211.56129
#> [273,] 1 218.36904
#> [274,] 1  87.53353
#> [275,] 1  68.98897
#> [276,] 1 139.76302
#> [277,] 1 170.09610
#> [278,] 1 222.71446
#> [279,] 1 220.29118
#> [280,] 1 189.55623
#> [281,] 1 178.79443
#> [282,] 1 180.93943
#> [283,] 1 226.07097
#> [284,] 1 221.38743
#> [285,] 1 219.36592
#> [286,] 1 115.30421
#> [287,] 1 159.40026
#> [288,] 1 196.87519
#> [289,] 1 211.05911
#> [290,] 1  91.28800
#> [291,] 1 226.03233
#> [292,] 1 129.21527
#> [293,] 1 246.60140
#> [294,] 1 162.28438
#> [295,] 1 231.72289
#> [296,] 1 193.02675
#> [297,] 1  97.12728
#> [298,] 1  50.78104
#> [299,] 1 145.87610
#> [300,] 1 224.42663
#> [301,] 1 102.46545
#> [302,] 1 182.68091
#> [303,] 1 225.92894
#> [304,] 1 232.30105
#> [305,] 1 128.06369
#> [306,] 1 223.03014
#> [307,] 1 152.92372
#> [308,] 1 198.23979
#> [309,] 1 242.04132
#> [310,] 1 163.94199
#> [311,] 1 112.21990
#> [312,] 1 198.66033
#> [313,] 1 140.09459
#> [314,] 1 144.77836
#> [315,] 1 144.88331
#> [316,] 1 198.14111
#> [317,] 1  71.43851
#> [318,] 1 178.43616
#> [319,] 1 134.43680
#> [320,] 1 210.10185
#> [321,] 1 173.35765
#> [322,] 1  99.87367
#> [323,] 1 186.24467
#> [324,] 1 119.54773
#> [325,] 1 228.29274
#> [326,] 1 181.44789
#> [327,] 1 237.73309
#> [328,] 1  76.83550
#> [329,] 1 244.49201
#> [330,] 1 120.14970
#> [331,] 1  97.40005
#> [332,] 1 173.12576
#> [333,] 1 199.42674
#> [334,] 1 242.70368
#> [335,] 1 236.53693
#> [336,] 1 208.43735
#> [337,] 1 112.34692
#> [338,] 1  68.68269
#> [339,] 1  91.45877
#> [340,] 1  56.35327
#> [341,] 1 165.94110
#> [342,] 1  80.84097
#> [343,] 1  75.05410
#> [344,] 1  79.59716
#> [345,] 1 232.66853
#> [346,] 1 101.48608
#> [347,] 1 158.49306
#> [348,] 1 179.80449
#> [349,] 1  79.83887
#> [350,] 1 219.78809
#> [351,] 1 108.70102
#> [352,] 1 160.42840
#> [353,] 1 224.62697
#> [354,] 1 179.39689
#> [355,] 1 129.43668
#> [356,] 1  55.90669
#> [357,] 1 121.37183
#> [358,] 1 189.70893
#> [359,] 1 109.88967
#> [360,] 1 210.97440
#> [361,] 1 204.85582
#> [362,] 1  92.22704
#> [363,] 1 125.43268
#> [364,] 1 112.27473
#> [365,] 1 229.51475
#> [366,] 1 133.29229
#> [367,] 1 217.17680
#> [368,] 1 114.28795
#> [369,] 1  77.47934
#> [370,] 1 173.54258
#> [371,] 1 185.08330
#> [372,] 1 104.48642
#> [373,] 1  87.24139
#> [374,] 1 116.06527
#> [375,] 1  74.36400
#> [376,] 1  97.10611
#> [377,] 1 236.56933
#> [378,] 1 206.50828
#> [379,] 1 140.35303
#> [380,] 1  72.16001
#> [381,] 1 227.73558
#> [382,] 1 212.71749
#> [383,] 1  89.35735
#> [384,] 1 170.04448
#> [385,] 1  57.99159
#> [386,] 1 144.75240
#> [387,] 1 205.39299
#> [388,] 1 165.96658
#> [389,] 1 114.39835
#> [390,] 1 248.67768
#> [391,] 1 149.25387
#> [392,] 1 186.28968
#> [393,] 1 197.58453
#> [394,] 1 231.52259
#> [395,] 1 138.29584
#> [396,] 1 199.62484
#> [397,] 1 200.90358
#> [398,] 1 139.07191
#> [399,] 1 123.27521
#> [400,] 1  65.81940
#> [401,] 1  91.03903
#> [402,] 1 227.00016
#> [403,] 1 233.38434
#> [404,] 1 173.51287
#> [405,] 1 123.20821
#> [406,] 1 185.17732
#> [407,] 1 132.08393
#> [408,] 1 183.86706
#> [409,] 1 232.02988
#> [410,] 1 132.97508
#> [411,] 1  80.59033
#> [412,] 1 125.49474
#> [413,] 1 143.15805
#> [414,] 1  98.85415
#> [415,] 1  73.64387
#> [416,] 1  51.65647
#> [417,] 1 180.17378
#> [418,] 1  61.31312
#> [419,] 1  76.02185
#> [420,] 1 242.13797
#> [421,] 1 101.91431
#> [422,] 1  51.81332
#> [423,] 1 248.57413
#> [424,] 1 180.58076
#> [425,] 1 194.89696
#> [426,] 1 192.85640
#> [427,] 1 215.00484
#> [428,] 1  79.64898
#> [429,] 1 185.00069
#> [430,] 1 219.37457
#> [431,] 1 248.51700
#> [432,] 1 110.81864
#> [433,] 1  79.07898
#> [434,] 1 153.80739
#> [435,] 1 216.43046
#> [436,] 1 233.63430
#> [437,] 1 119.62077
#> [438,] 1 116.53787
#> [439,] 1 217.77340
#> [440,] 1 139.24792
#> [441,] 1 188.91871
#> [442,] 1 230.56217
#> [443,] 1  55.89484
#> [444,] 1 144.36154
#> [445,] 1 131.77804
#> [446,] 1 117.38805
#> [447,] 1 182.65511
#> [448,] 1 224.62717
#> [449,] 1  67.35188
#> [450,] 1 116.92872
#> [451,] 1 236.74978
#> [452,] 1 233.71860
#> [453,] 1 187.35064
#> [454,] 1 126.70872
#> [455,] 1  51.79643
#> [456,] 1 193.98775
#> [457,] 1 146.18532
#> [458,] 1  50.74456
#> [459,] 1 164.42234
#> [460,] 1  66.13101
#> [461,] 1 125.97815
#> [462,] 1 249.90474
#> [463,] 1  69.49349
#> [464,] 1 210.84322
#> [465,] 1  66.84592
#> [466,] 1 225.43648
#> [467,] 1 246.50857
#> [468,] 1 171.97067
#> [469,] 1 186.96662
#> [470,] 1 148.91902
#> [471,] 1 105.19780
#> [472,] 1  50.74422
#> [473,] 1 182.88525
#> [474,] 1 159.65580
#> [475,] 1 169.20673
#> [476,] 1 111.66926
#> [477,] 1 229.45787
#> [478,] 1 233.23141
#> [479,] 1 244.33811
#> [480,] 1 118.47524
#> [481,] 1 235.68577
#> [482,] 1 233.72650
#> [483,] 1 188.28927
#> [484,] 1 203.98477
#> [485,] 1 170.43932
#> [486,] 1 203.86430
#> [487,] 1  69.59662
#> [488,] 1  96.35048
#> [489,] 1 191.36706
#> [490,] 1  55.76439
#> [491,] 1 176.22847
#> [492,] 1 184.43156
#> [493,] 1 140.57715
#> [494,] 1 185.17976
#> [495,] 1  51.87866
#> [496,] 1  62.69608
#> [497,] 1 105.84664
#> [498,] 1 143.57739
#> [499,] 1 205.29145
#> [500,] 1 123.38485
#> 
#> $y
#>   [1] 1 1 0 0 0 1 0 0 0 1 0 1 0 0 1 1 1 1 1 1 1 0 1 1 1 0 0 1 1 0 1 1 1 1 1 0 1
#>  [38] 1 1 0 1 0 1 1 0 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1
#>  [75] 1 1 1 0 1 1 1 1 1 1 0 1 0 1 0 0 1 1 1 1 1 1 1 0 1 0 1 1 0 1 1 1 1 1 0 1 1
#> [112] 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0
#> [149] 1 1 1 1 0 0 0 1 1 1 0 1 1 0 1 1 1 1 1 1 0 0 1 1 1 0 1 0 1 1 1 1 0 1 1 1 1
#> [186] 1 1 1 1 0 1 1 1 0 1 1 1 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1 0 1 1 0 1 1 1 0 1 0
#> [223] 1 0 1 1 0 1 0 0 1 1 0 1 1 1 1 0 1 1 0 1 1 1 1 1 1 0 1 1 1 0 1 1 1 1 1 1 1
#> [260] 1 1 1 1 1 1 1 0 1 1 1 0 0 1 1 1 1 1 0 0 1 1 1 1 0 1 1 1 1 0 1 0 1 0 1 0 0
#> [297] 1 0 1 0 0 1 0 0 1 0 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 0 1 1 1 1
#> [334] 0 1 1 1 1 0 1 1 1 0 1 0 1 1 0 1 0 1 1 1 1 1 0 1 1 1 1 1 1 1 1 0 1 0 1 0 1
#> [371] 1 1 0 1 1 1 1 0 1 1 0 0 0 1 1 0 0 1 1 1 1 1 0 1 1 1 1 1 1 1 1 0 0 1 1 1 1
#> [408] 1 0 1 1 1 1 1 0 0 1 1 1 0 1 1 0 1 0 1 1 0 0 0 0 1 0 1 1 0 1 1 0 1 1 0 1 1
#> [445] 1 1 0 1 0 1 0 1 0 1 1 1 1 1 1 1 1 0 0 1 1 0 0 1 0 1 1 1 1 1 1 1 0 0 0 1 0
#> [482] 0 0 1 0 1 1 1 0 1 1 1 1 1 0 1 0 1 0 1
#> 
#> $lambda
#> [1] 0.3173142 0.6826858
#> 
#> $beta
#>             comp.1      comp.2
#> beta.0 -11.5500856 18.23936639
#> beta.1   0.1113478 -0.09250477
#> 
#> $loglik
#> [1] -216.5086
#> 
#> $posterior
#>              comp.1       comp.2
#>   [1,] 9.140087e-01 8.599127e-02
#>   [2,] 7.838548e-02 9.216145e-01
#>   [3,] 8.453274e-06 9.999915e-01
#>   [4,] 2.502233e-05 9.999750e-01
#>   [5,] 5.373457e-07 9.999995e-01
#>   [6,] 2.597905e-01 7.402095e-01
#>   [7,] 9.999865e-01 1.352401e-05
#>   [8,] 5.396463e-07 9.999995e-01
#>   [9,] 2.072980e-07 9.999998e-01
#>  [10,] 3.724377e-01 6.275623e-01
#>  [11,] 3.321283e-05 9.999668e-01
#>  [12,] 3.098911e-01 6.901089e-01
#>  [13,] 9.999766e-01 2.344091e-05
#>  [14,] 3.198610e-04 9.996801e-01
#>  [15,] 4.652573e-01 5.347427e-01
#>  [16,] 3.142442e-01 6.857558e-01
#>  [17,] 4.998312e-02 9.500169e-01
#>  [18,] 3.772266e-01 6.227734e-01
#>  [19,] 1.797603e-01 8.202397e-01
#>  [20,] 2.756146e-01 7.243854e-01
#>  [21,] 9.530128e-02 9.046987e-01
#>  [22,] 9.999963e-01 3.668773e-06
#>  [23,] 2.949903e-01 7.050097e-01
#>  [24,] 3.223895e-01 6.776105e-01
#>  [25,] 3.817252e-01 6.182748e-01
#>  [26,] 3.281258e-05 9.999672e-01
#>  [27,] 2.314470e-07 9.999998e-01
#>  [28,] 4.327456e-02 9.567254e-01
#>  [29,] 2.617531e-01 7.382469e-01
#>  [30,] 9.999670e-01 3.303766e-05
#>  [31,] 3.466893e-01 6.533107e-01
#>  [32,] 2.672761e-01 7.327239e-01
#>  [33,] 3.541156e-01 6.458844e-01
#>  [34,] 2.380911e-01 7.619089e-01
#>  [35,] 6.961289e-03 9.930387e-01
#>  [36,] 5.127603e-04 9.994872e-01
#>  [37,] 5.346411e-01 4.653589e-01
#>  [38,] 3.210365e-01 6.789635e-01
#>  [39,] 3.192412e-01 6.807588e-01
#>  [40,] 2.164392e-06 9.999978e-01
#>  [41,] 3.570875e-01 6.429125e-01
#>  [42,] 2.274151e-07 9.999998e-01
#>  [43,] 3.369514e-01 6.630486e-01
#>  [44,] 3.149626e-01 6.850374e-01
#>  [45,] 1.323689e-07 9.999999e-01
#>  [46,] 3.147610e-01 6.852390e-01
#>  [47,] 3.585524e-01 6.414476e-01
#>  [48,] 3.305057e-01 6.694943e-01
#>  [49,] 9.575854e-01 4.241464e-02
#>  [50,] 2.912282e-01 7.087718e-01
#>  [51,] 1.124308e-06 9.999989e-01
#>  [52,] 3.116088e-01 6.883912e-01
#>  [53,] 3.152558e-01 6.847442e-01
#>  [54,] 3.121867e-01 6.878133e-01
#>  [55,] 3.372323e-01 6.627677e-01
#>  [56,] 3.321714e-01 6.678286e-01
#>  [57,] 6.123143e-01 3.876857e-01
#>  [58,] 3.213095e-01 6.786905e-01
#>  [59,] 5.612495e-01 4.387505e-01
#>  [60,] 3.035696e-01 6.964304e-01
#>  [61,] 3.164372e-01 6.835628e-01
#>  [62,] 3.175941e-01 6.824059e-01
#>  [63,] 9.809155e-01 1.908454e-02
#>  [64,] 3.084391e-01 6.915609e-01
#>  [65,] 9.819844e-01 1.801558e-02
#>  [66,] 1.029303e-05 9.999897e-01
#>  [67,] 3.168910e-01 6.831090e-01
#>  [68,] 3.157632e-01 6.842368e-01
#>  [69,] 9.222342e-01 7.776576e-02
#>  [70,] 1.820896e-01 8.179104e-01
#>  [71,] 5.254482e-02 9.474552e-01
#>  [72,] 3.025878e-01 6.974122e-01
#>  [73,] 3.191365e-01 6.808635e-01
#>  [74,] 1.497945e-01 8.502055e-01
#>  [75,] 2.946253e-01 7.053747e-01
#>  [76,] 3.257671e-01 6.742329e-01
#>  [77,] 9.348935e-02 9.065106e-01
#>  [78,] 7.010801e-06 9.999930e-01
#>  [79,] 3.475597e-01 6.524403e-01
#>  [80,] 4.758696e-01 5.241304e-01
#>  [81,] 3.097346e-01 6.902654e-01
#>  [82,] 3.256715e-01 6.743285e-01
#>  [83,] 1.682887e-01 8.317113e-01
#>  [84,] 3.124838e-01 6.875162e-01
#>  [85,] 9.999320e-01 6.803450e-05
#>  [86,] 3.356323e-01 6.643677e-01
#>  [87,] 1.946028e-07 9.999998e-01
#>  [88,] 3.137645e-01 6.862355e-01
#>  [89,] 2.766678e-05 9.999723e-01
#>  [90,] 9.999960e-01 3.970741e-06
#>  [91,] 4.991254e-02 9.500875e-01
#>  [92,] 3.482479e-01 6.517521e-01
#>  [93,] 4.479421e-02 9.552058e-01
#>  [94,] 2.842800e-01 7.157200e-01
#>  [95,] 6.529857e-02 9.347014e-01
#>  [96,] 9.026068e-01 9.739320e-02
#>  [97,] 1.378864e-01 8.621136e-01
#>  [98,] 1.092623e-07 9.999999e-01
#>  [99,] 2.444946e-03 9.975551e-01
#> [100,] 9.999797e-01 2.029841e-05
#> [101,] 1.495651e-01 8.504349e-01
#> [102,] 4.462397e-01 5.537603e-01
#> [103,] 9.999950e-01 4.976030e-06
#> [104,] 3.204876e-01 6.795124e-01
#> [105,] 3.849591e-01 6.150409e-01
#> [106,] 2.347872e-01 7.652128e-01
#> [107,] 2.992716e-01 7.007284e-01
#> [108,] 4.671909e-01 5.328091e-01
#> [109,] 1.770162e-07 9.999998e-01
#> [110,] 5.373873e-01 4.626127e-01
#> [111,] 3.260796e-01 6.739204e-01
#> [112,] 3.124038e-01 6.875962e-01
#> [113,] 2.851960e-01 7.148040e-01
#> [114,] 2.976543e-01 7.023457e-01
#> [115,] 8.911753e-02 9.108825e-01
#> [116,] 9.999628e-01 3.722327e-05
#> [117,] 2.993693e-01 7.006307e-01
#> [118,] 1.847389e-01 8.152611e-01
#> [119,] 4.127438e-01 5.872562e-01
#> [120,] 3.044018e-01 6.955982e-01
#> [121,] 1.839572e-01 8.160428e-01
#> [122,] 3.027532e-01 6.972468e-01
#> [123,] 7.808115e-02 9.219189e-01
#> [124,] 7.490305e-01 2.509695e-01
#> [125,] 3.180298e-01 6.819702e-01
#> [126,] 3.011825e-01 6.988175e-01
#> [127,] 3.244689e-01 6.755311e-01
#> [128,] 9.718439e-01 2.815609e-02
#> [129,] 3.548637e-01 6.451363e-01
#> [130,] 2.695159e-01 7.304841e-01
#> [131,] 9.940285e-01 5.971544e-03
#> [132,] 2.730521e-07 9.999997e-01
#> [133,] 2.966502e-01 7.033498e-01
#> [134,] 3.227217e-01 6.772783e-01
#> [135,] 3.165057e-01 6.834943e-01
#> [136,] 2.736964e-02 9.726304e-01
#> [137,] 1.411958e-01 8.588042e-01
#> [138,] 4.378966e-01 5.621034e-01
#> [139,] 2.309090e-01 7.690910e-01
#> [140,] 3.164817e-01 6.835183e-01
#> [141,] 2.031462e-01 7.968538e-01
#> [142,] 2.875815e-01 7.124185e-01
#> [143,] 3.095645e-01 6.904355e-01
#> [144,] 6.663913e-01 3.336087e-01
#> [145,] 3.173184e-01 6.826816e-01
#> [146,] 1.575087e-04 9.998425e-01
#> [147,] 2.254985e-06 9.999977e-01
#> [148,] 2.370225e-06 9.999976e-01
#> [149,] 3.002320e-01 6.997680e-01
#> [150,] 3.622104e-02 9.637790e-01
#> [151,] 3.479266e-01 6.520734e-01
#> [152,] 2.171543e-01 7.828457e-01
#> [153,] 3.709095e-07 9.999996e-01
#> [154,] 9.999479e-01 5.213679e-05
#> [155,] 1.719600e-07 9.999998e-01
#> [156,] 1.600051e-03 9.983999e-01
#> [157,] 4.195048e-01 5.804952e-01
#> [158,] 3.428599e-01 6.571401e-01
#> [159,] 1.483890e-05 9.999852e-01
#> [160,] 8.945626e-01 1.054374e-01
#> [161,] 3.164789e-01 6.835211e-01
#> [162,] 2.947974e-05 9.999705e-01
#> [163,] 9.391043e-01 6.089572e-02
#> [164,] 1.063966e-02 9.893603e-01
#> [165,] 3.152711e-01 6.847289e-01
#> [166,] 7.831613e-02 9.216839e-01
#> [167,] 9.813666e-01 1.863341e-02
#> [168,] 3.388263e-03 9.966117e-01
#> [169,] 9.997986e-01 2.014481e-04
#> [170,] 8.449142e-07 9.999992e-01
#> [171,] 1.847407e-02 9.815259e-01
#> [172,] 2.917011e-01 7.082989e-01
#> [173,] 4.271097e-02 9.572890e-01
#> [174,] 9.999346e-01 6.537522e-05
#> [175,] 9.725973e-01 2.740267e-02
#> [176,] 5.571815e-06 9.999944e-01
#> [177,] 9.616201e-01 3.837985e-02
#> [178,] 3.024790e-01 6.975210e-01
#> [179,] 8.102784e-01 1.897216e-01
#> [180,] 6.053580e-03 9.939464e-01
#> [181,] 9.977701e-01 2.229886e-03
#> [182,] 3.147714e-01 6.852286e-01
#> [183,] 3.522067e-01 6.477933e-01
#> [184,] 3.164299e-01 6.835701e-01
#> [185,] 6.480350e-01 3.519650e-01
#> [186,] 3.228370e-01 6.771630e-01
#> [187,] 2.835715e-01 7.164285e-01
#> [188,] 3.616511e-01 6.383489e-01
#> [189,] 1.403448e-01 8.596552e-01
#> [190,] 9.992955e-01 7.045235e-04
#> [191,] 3.171033e-01 6.828967e-01
#> [192,] 4.794958e-01 5.205042e-01
#> [193,] 5.930025e-01 4.069975e-01
#> [194,] 9.999767e-01 2.328576e-05
#> [195,] 3.350538e-01 6.649462e-01
#> [196,] 9.213379e-01 7.866205e-02
#> [197,] 3.448684e-01 6.551316e-01
#> [198,] 1.984449e-01 8.015551e-01
#> [199,] 2.831579e-01 7.168421e-01
#> [200,] 3.721305e-01 6.278695e-01
#> [201,] 5.956827e-07 9.999994e-01
#> [202,] 4.624034e-01 5.375966e-01
#> [203,] 4.472328e-07 9.999996e-01
#> [204,] 2.971287e-01 7.028713e-01
#> [205,] 8.150326e-01 1.849674e-01
#> [206,] 4.934074e-03 9.950659e-01
#> [207,] 1.648613e-01 8.351387e-01
#> [208,] 2.908152e-01 7.091848e-01
#> [209,] 2.875358e-01 7.124642e-01
#> [210,] 2.073984e-01 7.926016e-01
#> [211,] 2.992454e-01 7.007546e-01
#> [212,] 2.802042e-01 7.197958e-01
#> [213,] 9.989428e-01 1.057209e-03
#> [214,] 6.601380e-01 3.398620e-01
#> [215,] 9.816589e-01 1.834112e-02
#> [216,] 2.603274e-05 9.999740e-01
#> [217,] 3.319120e-01 6.680880e-01
#> [218,] 3.291182e-01 6.708818e-01
#> [219,] 3.262178e-01 6.737822e-01
#> [220,] 9.996593e-01 3.406851e-04
#> [221,] 3.115470e-01 6.884530e-01
#> [222,] 8.710732e-08 9.999999e-01
#> [223,] 8.837494e-03 9.911625e-01
#> [224,] 9.999929e-01 7.111013e-06
#> [225,] 3.150399e-01 6.849601e-01
#> [226,] 4.858197e-03 9.951418e-01
#> [227,] 2.295742e-07 9.999998e-01
#> [228,] 3.444225e-01 6.555775e-01
#> [229,] 9.991916e-01 8.083868e-04
#> [230,] 8.472248e-08 9.999999e-01
#> [231,] 2.865866e-01 7.134134e-01
#> [232,] 2.929131e-01 7.070869e-01
#> [233,] 9.942791e-01 5.720852e-03
#> [234,] 1.377666e-02 9.862233e-01
#> [235,] 3.256908e-01 6.743092e-01
#> [236,] 2.690939e-01 7.309061e-01
#> [237,] 1.687535e-03 9.983125e-01
#> [238,] 8.884172e-08 9.999999e-01
#> [239,] 2.917902e-01 7.082098e-01
#> [240,] 1.099611e-01 8.900389e-01
#> [241,] 3.507408e-05 9.999649e-01
#> [242,] 2.418033e-01 7.581967e-01
#> [243,] 3.030629e-01 6.969371e-01
#> [244,] 3.007343e-01 6.992657e-01
#> [245,] 3.099857e-01 6.900143e-01
#> [246,] 5.725072e-01 4.274928e-01
#> [247,] 9.434877e-02 9.056512e-01
#> [248,] 3.025457e-05 9.999697e-01
#> [249,] 3.269258e-01 6.730742e-01
#> [250,] 2.614630e-01 7.385370e-01
#> [251,] 2.942987e-01 7.057013e-01
#> [252,] 9.999955e-01 4.467853e-06
#> [253,] 3.141909e-01 6.858091e-01
#> [254,] 9.713965e-01 2.860349e-02
#> [255,] 1.571027e-03 9.984290e-01
#> [256,] 1.414738e-02 9.858526e-01
#> [257,] 3.098816e-01 6.901184e-01
#> [258,] 2.490688e-01 7.509312e-01
#> [259,] 9.720230e-01 2.797698e-02
#> [260,] 3.269054e-01 6.730946e-01
#> [261,] 4.704632e-01 5.295368e-01
#> [262,] 3.653830e-01 6.346170e-01
#> [263,] 4.474664e-01 5.525336e-01
#> [264,] 1.575417e-02 9.842458e-01
#> [265,] 1.074611e-01 8.925389e-01
#> [266,] 3.392311e-01 6.607689e-01
#> [267,] 1.897219e-07 9.999998e-01
#> [268,] 6.954741e-01 3.045259e-01
#> [269,] 2.488237e-03 9.975118e-01
#> [270,] 3.846445e-01 6.153555e-01
#> [271,] 3.378294e-06 9.999966e-01
#> [272,] 5.947196e-06 9.999941e-01
#> [273,] 7.828600e-01 2.171400e-01
#> [274,] 6.667435e-02 9.333256e-01
#> [275,] 1.135959e-02 9.886404e-01
#> [276,] 3.109515e-01 6.890485e-01
#> [277,] 3.310129e-01 6.689871e-01
#> [278,] 1.566915e-06 9.999984e-01
#> [279,] 2.072435e-06 9.999979e-01
#> [280,] 4.044757e-01 5.955243e-01
#> [281,] 3.507195e-01 6.492805e-01
#> [282,] 3.581906e-01 6.418094e-01
#> [283,] 8.727889e-01 1.272111e-01
#> [284,] 1.825182e-06 9.999982e-01
#> [285,] 7.962650e-01 2.037350e-01
#> [286,] 2.633819e-01 7.366181e-01
#> [287,] 3.201810e-01 6.798190e-01
#> [288,] 4.714603e-01 5.285397e-01
#> [289,] 6.337057e-06 9.999937e-01
#> [290,] 9.001490e-02 9.099851e-01
#> [291,] 1.075410e-06 9.999989e-01
#> [292,] 3.014483e-01 6.985517e-01
#> [293,] 1.138971e-07 9.999999e-01
#> [294,] 3.222470e-01 6.777530e-01
#> [295,] 5.712308e-07 9.999994e-01
#> [296,] 8.403468e-05 9.999160e-01
#> [297,] 1.343622e-01 8.656378e-01
#> [298,] 9.999971e-01 2.914697e-06
#> [299,] 3.138638e-01 6.861362e-01
#> [300,] 1.289214e-06 9.999987e-01
#> [301,] 9.993514e-01 6.486234e-04
#> [302,] 3.652761e-01 6.347239e-01
#> [303,] 1.087993e-06 9.999989e-01
#> [304,] 5.360435e-07 9.999995e-01
#> [305,] 2.997566e-01 7.002434e-01
#> [306,] 1.511341e-06 9.999985e-01
#> [307,] 3.167764e-01 6.832236e-01
#> [308,] 4.872181e-01 5.127819e-01
#> [309,] 1.859710e-07 9.999998e-01
#> [310,] 3.236636e-01 6.763364e-01
#> [311,] 2.477369e-01 7.522631e-01
#> [312,] 4.922802e-01 5.077198e-01
#> [313,] 3.111367e-01 6.888633e-01
#> [314,] 3.133984e-01 6.866016e-01
#> [315,] 3.134436e-01 6.865564e-01
#> [316,] 4.860443e-01 5.139557e-01
#> [317,] 1.458160e-02 9.854184e-01
#> [318,] 3.495940e-01 6.504060e-01
#> [319,] 3.072262e-01 6.927738e-01
#> [320,] 6.583078e-01 3.416922e-01
#> [321,] 3.367748e-01 6.632252e-01
#> [322,] 1.571494e-01 8.428506e-01
#> [323,] 3.831272e-01 6.168728e-01
#> [324,] 2.799448e-01 7.200552e-01
#> [325,] 8.350404e-07 9.999992e-01
#> [326,] 3.601591e-01 6.398409e-01
#> [327,] 9.505613e-01 4.943872e-02
#> [328,] 2.498202e-02 9.750180e-01
#> [329,] 1.428521e-07 9.999999e-01
#> [330,] 2.818752e-01 7.181248e-01
#> [331,] 1.365979e-01 8.634021e-01
#> [332,] 3.363103e-01 6.636897e-01
#> [333,] 5.017499e-01 4.982501e-01
#> [334,] 1.731616e-07 9.999998e-01
#> [335,] 9.452558e-01 5.474422e-02
#> [336,] 6.320411e-01 3.679589e-01
#> [337,] 2.484447e-01 7.515553e-01
#> [338,] 1.100845e-02 9.889916e-01
#> [339,] 9.998418e-01 1.582486e-04
#> [340,] 3.046378e-03 9.969536e-01
#> [341,] 3.256485e-01 6.743515e-01
#> [342,] 3.669457e-02 9.633054e-01
#> [343,] 9.999714e-01 2.856980e-05
#> [344,] 3.262150e-02 9.673785e-01
#> [345,] 5.148424e-07 9.999995e-01
#> [346,] 1.705919e-01 8.294081e-01
#> [347,] 3.196173e-01 6.803827e-01
#> [348,] 8.333077e-04 9.991667e-01
#> [349,] 3.338040e-02 9.666196e-01
#> [350,] 2.197574e-06 9.999978e-01
#> [351,] 2.259670e-01 7.740330e-01
#> [352,] 3.208662e-01 6.791338e-01
#> [353,] 8.584106e-01 1.415894e-01
#> [354,] 3.526882e-01 6.473118e-01
#> [355,] 3.017534e-01 6.982466e-01
#> [356,] 9.999953e-01 4.688607e-06
#> [357,] 2.855075e-01 7.144925e-01
#> [358,] 4.055842e-01 5.944158e-01
#> [359,] 2.337800e-01 7.662200e-01
#> [360,] 6.720915e-01 3.279085e-01
#> [361,] 5.768977e-01 4.231023e-01
#> [362,] 9.656212e-02 9.034379e-01
#> [363,] 2.951487e-01 7.048513e-01
#> [364,] 2.480431e-01 7.519569e-01
#> [365,] 7.290104e-07 9.999993e-01
#> [366,] 3.061827e-01 6.938173e-01
#> [367,] 2.990163e-06 9.999970e-01
#> [368,] 2.585794e-01 7.414206e-01
#> [369,] 9.999638e-01 3.622093e-05
#> [370,] 3.371519e-01 6.628481e-01
#> [371,] 3.767726e-01 6.232274e-01
#> [372,] 1.949493e-01 8.050507e-01
#> [373,] 9.999012e-01 9.878616e-05
#> [374,] 2.667580e-01 7.332420e-01
#> [375,] 1.956934e-02 9.804307e-01
#> [376,] 1.341891e-01 8.658109e-01
#> [377,] 9.454061e-01 5.459393e-02
#> [378,] 1.147148e-05 9.999885e-01
#> [379,] 3.112781e-01 6.887219e-01
#> [380,] 1.568595e-02 9.843140e-01
#> [381,] 8.885659e-07 9.999991e-01
#> [382,] 5.145332e-06 9.999949e-01
#> [383,] 9.998753e-01 1.246641e-04
#> [384,] 3.309340e-01 6.690660e-01
#> [385,] 3.619244e-03 9.963808e-01
#> [386,] 4.221783e-01 5.778217e-01
#> [387,] 1.333949e-05 9.999867e-01
#> [388,] 3.256760e-01 6.743240e-01
#> [389,] 2.591176e-01 7.408824e-01
#> [390,] 9.811161e-01 1.888395e-02
#> [391,] 3.152398e-01 6.847602e-01
#> [392,] 3.833846e-01 6.166154e-01
#> [393,] 4.108698e-05 9.999589e-01
#> [394,] 9.169677e-01 8.303229e-02
#> [395,] 3.100772e-01 6.899228e-01
#> [396,] 5.042480e-01 4.957520e-01
#> [397,] 5.208576e-01 4.791424e-01
#> [398,] 3.105514e-01 6.894486e-01
#> [399,] 2.904576e-01 7.095424e-01
#> [400,] 8.195018e-03 9.918050e-01
#> [401,] 8.832423e-02 9.116758e-01
#> [402,] 9.647179e-07 9.999990e-01
#> [403,] 4.759775e-07 9.999995e-01
#> [404,] 3.370909e-01 6.629091e-01
#> [405,] 2.902970e-01 7.097030e-01
#> [406,] 3.772668e-01 6.227332e-01
#> [407,] 3.049583e-01 6.950417e-01
#> [408,] 3.706873e-01 6.293127e-01
#> [409,] 5.522614e-07 9.999994e-01
#> [410,] 3.058741e-01 6.941259e-01
#> [411,] 3.583979e-02 9.641602e-01
#> [412,] 2.952706e-01 7.047294e-01
#> [413,] 3.126769e-01 6.873231e-01
#> [414,] 1.486382e-01 8.513618e-01
#> [415,] 9.999751e-01 2.492274e-05
#> [416,] 9.999968e-01 3.160912e-06
#> [417,] 3.553737e-01 6.446263e-01
#> [418,] 5.126790e-03 9.948732e-01
#> [419,] 2.306393e-02 9.769361e-01
#> [420,] 1.840438e-07 9.999998e-01
#> [421,] 1.741373e-01 8.258627e-01
#> [422,] 1.887163e-03 9.981128e-01
#> [423,] 9.218700e-08 9.999999e-01
#> [424,] 3.568494e-01 6.431506e-01
#> [425,] 6.232433e-05 9.999377e-01
#> [426,] 4.310854e-01 5.689146e-01
#> [427,] 7.344623e-01 2.655377e-01
#> [428,] 9.999551e-01 4.492775e-05
#> [429,] 3.271486e-04 9.996729e-01
#> [430,] 2.306443e-06 9.999977e-01
#> [431,] 9.275288e-08 9.999999e-01
#> [432,] 2.395636e-01 7.604364e-01
#> [433,] 9.999576e-01 4.244192e-05
#> [434,] 3.171734e-01 6.828266e-01
#> [435,] 7.555107e-01 2.444893e-01
#> [436,] 4.631253e-07 9.999995e-01
#> [437,] 2.801842e-01 7.198158e-01
#> [438,] 2.687615e-01 7.312385e-01
#> [439,] 2.785402e-06 9.999972e-01
#> [440,] 3.106552e-01 6.893448e-01
#> [441,] 3.999707e-01 6.000293e-01
#> [442,] 6.492230e-07 9.999994e-01
#> [443,] 2.902823e-03 9.970972e-01
#> [444,] 3.132173e-01 6.867827e-01
#> [445,] 3.046265e-01 6.953735e-01
#> [446,] 2.721913e-01 7.278087e-01
#> [447,] 4.966969e-04 9.995033e-01
#> [448,] 8.584126e-01 1.415874e-01
#> [449,] 9.999863e-01 1.367557e-05
#> [450,] 2.703658e-01 7.296342e-01
#> [451,] 3.297024e-07 9.999997e-01
#> [452,] 9.306503e-01 6.934967e-02
#> [453,] 2.171447e-04 9.997829e-01
#> [454,] 2.975221e-01 7.024779e-01
#> [455,] 1.883799e-03 9.981162e-01
#> [456,] 4.415430e-01 5.584570e-01
#> [457,] 3.139923e-01 6.860077e-01
#> [458,] 1.685581e-03 9.983144e-01
#> [459,] 3.241110e-01 6.758890e-01
#> [460,] 8.463585e-03 9.915364e-01
#> [461,] 2.961971e-01 7.038029e-01
#> [462,] 7.994561e-08 9.999999e-01
#> [463,] 9.999832e-01 1.675171e-05
#> [464,] 6.700212e-01 3.299788e-01
#> [465,] 9.112475e-03 9.908875e-01
#> [466,] 1.150069e-06 9.999988e-01
#> [467,] 1.150371e-07 9.999999e-01
#> [468,] 3.341279e-01 6.658721e-01
#> [469,] 2.320423e-04 9.997680e-01
#> [470,] 3.151044e-01 6.848956e-01
#> [471,] 2.004999e-01 7.995001e-01
#> [472,] 1.685521e-03 9.983145e-01
#> [473,] 3.661731e-01 6.338269e-01
#> [474,] 3.203465e-01 6.796535e-01
#> [475,] 3.297004e-01 6.702996e-01
#> [476,] 2.446047e-01 7.553953e-01
#> [477,] 7.336233e-07 9.999993e-01
#> [478,] 4.840202e-07 9.999995e-01
#> [479,] 1.452353e-07 9.999999e-01
#> [480,] 2.762612e-01 7.237388e-01
#> [481,] 3.701751e-07 9.999996e-01
#> [482,] 4.584749e-07 9.999995e-01
#> [483,] 1.848329e-04 9.998152e-01
#> [484,] 5.640115e-01 4.359885e-01
#> [485,] 4.820175e-03 9.951798e-01
#> [486,] 5.622504e-01 4.377496e-01
#> [487,] 1.208842e-02 9.879116e-01
#> [488,] 1.280496e-01 8.719504e-01
#> [489,] 1.102146e-04 9.998898e-01
#> [490,] 2.863212e-03 9.971368e-01
#> [491,] 3.433481e-01 6.566519e-01
#> [492,] 3.734417e-01 6.265583e-01
#> [493,] 3.113988e-01 6.886012e-01
#> [494,] 3.772797e-01 6.227203e-01
#> [495,] 9.999968e-01 3.226662e-06
#> [496,] 5.923390e-03 9.940766e-01
#> [497,] 9.989328e-01 1.067216e-03
#> [498,] 3.128684e-01 6.871316e-01
#> [499,] 1.352551e-05 9.999865e-01
#> [500,] 2.907184e-01 7.092816e-01
#> 
#> $all.loglik
#> [1] -217.9542 -216.7515 -216.5812 -216.5086
#> 
#> $restarts
#> [1] 0
#> 
#> $ft
#> [1] "logisregmixEM"
#> 
#> attr(,"class")
#> [1] "mixEM"