```Mplus VERSION 8.8
MUTHEN & MUTHEN
04/19/2022  11:13 PM

INPUT INSTRUCTIONS

TITLE:	this is an example of mixture modeling
with known classes (multiple group
analysis)
DATA:	FILE IS ex7.21.dat;
VARIABLE:	NAMES = g y1-y4;
CLASSES = cg (2) c (2);
KNOWNCLASS = cg (g = 0 g = 1);
ANALYSIS:	TYPE = MIXTURE;
MODEL:
%OVERALL%
c ON cg;
MODEL c:
%c#1%
[y1-y4];
%c#2%
[y1-y4];
MODEL cg:
%cg#1%
y1-y4;
%cg#2%
y1-y4;
OUTPUT:	TECH1 TECH8;

*** WARNING in MODEL command
All variables are uncorrelated with all other variables within class.
Check that this is what is intended.
1 WARNING(S) FOUND IN THE INPUT INSTRUCTIONS

this is an example of mixture modeling
with known classes (multiple group
analysis)

SUMMARY OF ANALYSIS

Number of groups                                                 1
Number of observations                                        1000

Number of dependent variables                                    4
Number of independent variables                                  0
Number of continuous latent variables                            0
Number of categorical latent variables                           2

Observed dependent variables

Continuous
Y1          Y2          Y3          Y4

Categorical latent variables
CG          C

Knownclass            CG

Estimator                                                      MLR
Information matrix                                        OBSERVED
Optimization Specifications for the Quasi-Newton Algorithm for
Continuous Outcomes
Maximum number of iterations                                 100
Convergence criterion                                  0.100D-05
Optimization Specifications for the EM Algorithm
Maximum number of iterations                                 500
Convergence criteria
Loglikelihood change                                 0.100D-06
Relative loglikelihood change                        0.100D-06
Derivative                                           0.100D-05
Optimization Specifications for the M step of the EM Algorithm for
Categorical Latent variables
Number of M step iterations                                    1
M step convergence criterion                           0.100D-05
Basis for M step termination                           ITERATION
Optimization Specifications for the M step of the EM Algorithm for
Censored, Binary or Ordered Categorical (Ordinal), Unordered
Categorical (Nominal) and Count Outcomes
Number of M step iterations                                    1
M step convergence criterion                           0.100D-05
Basis for M step termination                           ITERATION
Maximum value for logit thresholds                            15
Minimum value for logit thresholds                           -15
Minimum expected cell size for chi-square              0.100D-01
Optimization algorithm                                         EMA
Random Starts Specifications
Number of initial stage random starts                         20
Number of final stage optimizations                            4
Number of initial stage iterations                            10
Initial stage convergence criterion                    0.100D+01
Random starts scale                                    0.500D+01
Random seed for generating random starts                       0
Parameterization                                             LOGIT

Input data file(s)
ex7.21.dat
Input data format  FREE

UNIVARIATE SAMPLE STATISTICS

UNIVARIATE HIGHER-ORDER MOMENT DESCRIPTIVE STATISTICS

Variable/         Mean/     Skewness/   Minimum/ % with                Percentiles
Sample Size      Variance    Kurtosis    Maximum  Min/Max      20%/60%    40%/80%    Median

Y1                   -0.239       0.063      -4.054    0.10%      -1.370     -0.612     -0.301
1000.000       1.628      -0.459       3.196    0.10%       0.070      0.924
Y2                   -0.261       0.106      -3.834    0.10%      -1.418     -0.661     -0.304
1000.000       1.542      -0.482       4.215    0.10%       0.052      0.877
Y3                   -0.262       0.087      -4.511    0.10%      -1.401     -0.743     -0.385
1000.000       1.689      -0.538       3.201    0.10%       0.083      0.918
Y4                   -0.256       0.146      -3.351    0.10%      -1.409     -0.777     -0.361
1000.000       1.704      -0.723       3.291    0.10%       0.066      1.040

RANDOM STARTS RESULTS RANKED FROM THE BEST TO THE WORST LOGLIKELIHOOD VALUES

Final stage loglikelihood values at local maxima, seeds, and initial stage start numbers:

-6273.830  285380           1
-6273.830  27071            15
-6273.830  573096           20
-6273.830  107446           12

THE BEST LOGLIKELIHOOD VALUE HAS BEEN REPLICATED.  RERUN WITH AT LEAST TWICE THE
RANDOM STARTS TO CHECK THAT THE BEST LOGLIKELIHOOD IS STILL OBTAINED AND REPLICATED.

THE MODEL ESTIMATION TERMINATED NORMALLY

MODEL FIT INFORMATION

Number of Free Parameters                       19

Loglikelihood

H0 Value                       -6273.830
H0 Scaling Correction Factor      0.9749
for MLR

Information Criteria

Akaike (AIC)                   12585.660
Bayesian (BIC)                 12678.907
(n* = (n + 2) / 24)

FINAL CLASS COUNTS AND PROPORTIONS FOR EACH LATENT CLASS VARIABLE
BASED ON THE ESTIMATED MODEL

Latent Class
Variable    Class

CG             1       513.00000          0.51300
2       487.00000          0.48700
C              1       622.02063          0.62202
2       377.97937          0.37798

LATENT CLASS INDICATOR MEANS AND PROBABILITIES FOR EACH LATENT CLASS

MEAN/PROBABILITY PROFILES FOR C
Latent class
1      2
Y1           -0.960  0.938
Y2           -0.957  0.905
Y3           -1.010  0.970
Y4           -1.041  1.008

LATENT TRANSITION PROBABILITIES BASED ON THE ESTIMATED MODEL

CG Classes (Rows) by C Classes (Columns)

1        2

1     0.754    0.246
2     0.483    0.517

TRANSITION PROBABILITY ODDS

TRANSITION TABLE ODDS AND 95% CONFIDENCE INTERVALS FOR CG TO C
1.000(1.000,1.000)   0.326(0.264,0.401)
0.933(0.780,1.115)   1.000(1.000,1.000)

C-SPECIFIC CLASSIFICATION RESULTS

Classification Quality for CG

Entropy                         1.000

Average Latent Class Probabilities for Most Likely Latent Class Membership (Row)
by Latent Class (Column)

1        2

1   1.000    0.000
2   0.000    1.000

Classification Probabilities for the Most Likely Latent Class Membership (Column)
by Latent Class (Row)

1        2

1   1.000    0.000
2   0.000    1.000

Logits for the Classification Probabilities for the Most Likely Latent Class Membership (Column)
by Latent Class (Row)

1        2

1     13.816    0.000
2    -13.816    0.000

Classification Quality for C

Entropy                         0.961

Average Latent Class Probabilities for Most Likely Latent Class Membership (Row)
by Latent Class (Column)

1        2

1   0.993    0.007
2   0.011    0.989

Classification Probabilities for the Most Likely Latent Class Membership (Column)
by Latent Class (Row)

1        2

1   0.993    0.007
2   0.011    0.989

Logits for the Classification Probabilities for the Most Likely Latent Class Membership (Column)
by Latent Class (Row)

1        2

1      4.975    0.000
2     -4.477    0.000

MODEL RESULTS

Two-Tailed
Estimate       S.E.  Est./S.E.    P-Value

Parameters for Class-specific Model Parts of CG

Latent Class CG#1

Variances
Y1                 1.021      0.066     15.466      0.000
Y2                 0.986      0.065     15.246      0.000
Y3                 0.990      0.063     15.824      0.000
Y4                 1.001      0.060     16.601      0.000

Latent Class CG#2

Variances
Y1                 0.551      0.035     15.642      0.000
Y2                 0.447      0.027     16.534      0.000
Y3                 0.514      0.031     16.337      0.000
Y4                 0.465      0.030     15.428      0.000

Parameters for Class-specific Model Parts of C

Latent Class C#1

Means
Y1                -0.960      0.036    -26.726      0.000
Y2                -0.957      0.033    -28.712      0.000
Y3                -1.010      0.034    -29.435      0.000
Y4                -1.041      0.034    -30.998      0.000

Latent Class C#2

Means
Y1                 0.938      0.042     22.595      0.000
Y2                 0.905      0.039     23.449      0.000
Y3                 0.970      0.041     23.425      0.000
Y4                 1.008      0.040     25.270      0.000

Categorical Latent Variables

C#1      ON
CG#1               1.192      0.140      8.502      0.000

Means
CG#1               0.052      0.063      0.822      0.411
C#1               -0.070      0.091     -0.765      0.444

QUALITY OF NUMERICAL RESULTS

Condition Number for the Information Matrix              0.345E-01
(ratio of smallest to largest eigenvalue)

TECHNICAL 1 OUTPUT

PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 1 1

NU
Y1            Y2            Y3            Y4
________      ________      ________      ________
1             2             3             4

THETA
Y1            Y2            Y3            Y4
________      ________      ________      ________
Y1                 5
Y2                 0             6
Y3                 0             0             7
Y4                 0             0             0             8

PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 1 2

NU
Y1            Y2            Y3            Y4
________      ________      ________      ________
9            10            11            12

THETA
Y1            Y2            Y3            Y4
________      ________      ________      ________
Y1                 5
Y2                 0             6
Y3                 0             0             7
Y4                 0             0             0             8

PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 2 1

NU
Y1            Y2            Y3            Y4
________      ________      ________      ________
1             2             3             4

THETA
Y1            Y2            Y3            Y4
________      ________      ________      ________
Y1                13
Y2                 0            14
Y3                 0             0            15
Y4                 0             0             0            16

PARAMETER SPECIFICATION FOR LATENT CLASS PATTERN 2 2

NU
Y1            Y2            Y3            Y4
________      ________      ________      ________
9            10            11            12

THETA
Y1            Y2            Y3            Y4
________      ________      ________      ________
Y1                13
Y2                 0            14
Y3                 0             0            15
Y4                 0             0             0            16

PARAMETER SPECIFICATION FOR LATENT CLASS REGRESSION MODEL PART

ALPHA(C)
CG#1          CG#2          C#1           C#2
________      ________      ________      ________
17             0            18             0

BETA(C)
CG#1          CG#2
________      ________
C#1               19             0
C#2                0             0

STARTING VALUES FOR LATENT CLASS PATTERN 1 1

NU
Y1            Y2            Y3            Y4
________      ________      ________      ________
-0.877        -0.882        -0.912        -0.908

THETA
Y1            Y2            Y3            Y4
________      ________      ________      ________
Y1             0.814
Y2             0.000         0.771
Y3             0.000         0.000         0.844
Y4             0.000         0.000         0.000         0.852

STARTING VALUES FOR LATENT CLASS PATTERN 1 2

NU
Y1            Y2            Y3            Y4
________      ________      ________      ________
0.399         0.359         0.388         0.397

THETA
Y1            Y2            Y3            Y4
________      ________      ________      ________
Y1             0.814
Y2             0.000         0.771
Y3             0.000         0.000         0.844
Y4             0.000         0.000         0.000         0.852

STARTING VALUES FOR LATENT CLASS PATTERN 2 1

NU
Y1            Y2            Y3            Y4
________      ________      ________      ________
-0.877        -0.882        -0.912        -0.908

THETA
Y1            Y2            Y3            Y4
________      ________      ________      ________
Y1             0.814
Y2             0.000         0.771
Y3             0.000         0.000         0.844
Y4             0.000         0.000         0.000         0.852

STARTING VALUES FOR LATENT CLASS PATTERN 2 2

NU
Y1            Y2            Y3            Y4
________      ________      ________      ________
0.399         0.359         0.388         0.397

THETA
Y1            Y2            Y3            Y4
________      ________      ________      ________
Y1             0.814
Y2             0.000         0.771
Y3             0.000         0.000         0.844
Y4             0.000         0.000         0.000         0.852

STARTING VALUES FOR LATENT CLASS REGRESSION MODEL PART

ALPHA(C)
CG#1          CG#2          C#1           C#2
________      ________      ________      ________
0.000         0.000         0.000         0.000

BETA(C)
CG#1          CG#2
________      ________
C#1            0.000         0.000
C#2            0.000         0.000

TECHNICAL 8 OUTPUT

INITIAL STAGE ITERATIONS

TECHNICAL 8 OUTPUT FOR UNPERTURBED STARTING VALUE SET

E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
1 -0.67363796D+04    0.0000000    0.0000000  EM
2 -0.63000443D+04  436.3353227    0.0647730  EM
3 -0.62745672D+04   25.4771637    0.0040440  EM
4 -0.62738481D+04    0.7190546    0.0001146  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 1

E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
1 -0.11247895D+05    0.0000000    0.0000000  EM
2 -0.66505874D+04 4597.3080515    0.4087261  EM
3 -0.63209241D+04  329.6632402    0.0495690  EM
4 -0.62750152D+04   45.9089343    0.0072630  EM
5 -0.62738528D+04    1.1623940    0.0001852  EM
6 -0.62738304D+04    0.0224044    0.0000036  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 2

E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
1 -0.18887676D+05    0.0000000    0.0000000  EM
2 -0.73423781D+04 ************    0.6112609  EM
3 -0.72229451D+04  119.4330277    0.0162663  EM
4 -0.70963279D+04  126.6172068    0.0175299  EM
5 -0.68892220D+04  207.1058322    0.0291849  EM
6 -0.65571616D+04  332.0604275    0.0482000  EM
7 -0.63069585D+04  250.2031156    0.0381572  EM
8 -0.62748289D+04   32.1295602    0.0050943  EM
9 -0.62738547D+04    0.9742502    0.0001553  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 3

E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
1 -0.16480211D+05    0.0000000    0.0000000  EM
2 -0.73879744D+04 9092.2367389    0.5517063  EM
3 -0.71448348D+04  243.1396133    0.0329102  EM
4 -0.67350642D+04  409.7705886    0.0573520  EM
5 -0.63555156D+04  379.5485636    0.0563541  EM
6 -0.62762511D+04   79.2645549    0.0124718  EM
7 -0.62738859D+04    2.3651817    0.0003768  EM
8 -0.62738313D+04    0.0545795    0.0000087  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 4

E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
1 -0.15452706D+05    0.0000000    0.0000000  EM
2 -0.73522180D+04 8100.4882367    0.5242116  EM
3 -0.72615122D+04   90.7058267    0.0123372  EM
4 -0.71510046D+04  110.5075563    0.0152183  EM
5 -0.69754198D+04  175.5848273    0.0245539  EM
6 -0.66797018D+04  295.7180355    0.0423943  EM
7 -0.63590578D+04  320.6439376    0.0480027  EM
8 -0.62773733D+04   81.6845710    0.0128454  EM
9 -0.62739185D+04    3.4548134    0.0005504  EM
10 -0.62738321D+04    0.0863407    0.0000138  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 5

E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
1 -0.11047689D+05    0.0000000    0.0000000  EM
2 -0.73633673D+04 3684.3215058    0.3334925  EM
3 -0.72959164D+04   67.4508718    0.0091603  EM
4 -0.72130966D+04   82.8198164    0.0113515  EM
5 -0.70853759D+04  127.7206801    0.0177068  EM
6 -0.68686503D+04  216.7256532    0.0305877  EM
7 -0.65308128D+04  337.8374340    0.0491854  EM
8 -0.63007376D+04  230.0752719    0.0352292  EM
9 -0.62746101D+04   26.1274634    0.0041467  EM
10 -0.62738490D+04    0.7610923    0.0001213  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 6

E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
1 -0.18258359D+05    0.0000000    0.0000000  EM
2 -0.66145625D+04 ************    0.6377242  EM
3 -0.63292266D+04  285.3358446    0.0431375  EM
4 -0.62755410D+04   53.6856661    0.0084822  EM
5 -0.62738623D+04    1.6786232    0.0002675  EM
6 -0.62738306D+04    0.0317490    0.0000051  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 7

E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
1 -0.20833427D+05    0.0000000    0.0000000  EM
2 -0.69728021D+04 ************    0.6653070  EM
3 -0.64870675D+04  485.7345941    0.0696613  EM
4 -0.62845589D+04  202.5086459    0.0312173  EM
5 -0.62741103D+04   10.4486084    0.0016626  EM
6 -0.62738372D+04    0.2730814    0.0000435  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 8

E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
1 -0.12063212D+05    0.0000000    0.0000000  EM
2 -0.69967767D+04 5066.4354633    0.4199906  EM
3 -0.65476949D+04  449.0817622    0.0641841  EM
4 -0.62906732D+04  257.0217079    0.0392538  EM
5 -0.62742465D+04   16.4267014    0.0026113  EM
6 -0.62738405D+04    0.4060477    0.0000647  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 9

E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
1 -0.19235086D+05    0.0000000    0.0000000  EM
2 -0.63873658D+04 ************    0.6679315  EM
3 -0.62761982D+04  111.1675861    0.0174043  EM
4 -0.62738757D+04    2.3225109    0.0003701  EM
5 -0.62738310D+04    0.0447423    0.0000071  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 10

E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
1 -0.12302613D+05    0.0000000    0.0000000  EM
2 -0.72390453D+04 5063.5673215    0.4115847  EM
3 -0.69148631D+04  324.1822171    0.0447825  EM
4 -0.64716114D+04  443.2516976    0.0641013  EM
5 -0.62841805D+04  187.4309815    0.0289620  EM
6 -0.62740997D+04   10.0807236    0.0016041  EM
7 -0.62738369D+04    0.2627806    0.0000419  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 11

E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
1 -0.21933803D+05    0.0000000    0.0000000  EM
2 -0.63459081D+04 ************    0.7106791  EM
3 -0.62761604D+04   69.7476400    0.0109910  EM
4 -0.62738785D+04    2.2818830    0.0003636  EM
5 -0.62738310D+04    0.0475774    0.0000076  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 12

E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
1 -0.12943657D+05    0.0000000    0.0000000  EM
2 -0.63194830D+04 6624.1735734    0.5117699  EM
3 -0.62749514D+04   44.5316313    0.0070467  EM
4 -0.62738496D+04    1.1017559    0.0001756  EM
5 -0.62738302D+04    0.0193840    0.0000031  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 13

E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
1 -0.17818315D+05    0.0000000    0.0000000  EM
2 -0.71850864D+04 ************    0.5967584  EM
3 -0.69319881D+04  253.0983140    0.0352255  EM
4 -0.65979979D+04  333.9902002    0.0481810  EM
5 -0.63189277D+04  279.0702361    0.0422962  EM
6 -0.62752909D+04   43.6367847    0.0069057  EM
7 -0.62738670D+04    1.4239374    0.0002269  EM
8 -0.62738309D+04    0.0361012    0.0000058  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 14

E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
1 -0.25290132D+05    0.0000000    0.0000000  EM
2 -0.67199349D+04 ************    0.7342863  EM
3 -0.63118822D+04  408.0527565    0.0607227  EM
4 -0.62748062D+04   37.0759504    0.0058740  EM
5 -0.62738554D+04    0.9508111    0.0001515  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 15

E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
1 -0.15304831D+05    0.0000000    0.0000000  EM
2 -0.64203360D+04 8884.4949154    0.5805027  EM
3 -0.62760483D+04  144.2877423    0.0224735  EM
4 -0.62738504D+04    2.1979054    0.0003502  EM
5 -0.62738301D+04    0.0202503    0.0000032  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 16

E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
1 -0.20047288D+05    0.0000000    0.0000000  EM
2 -0.74341164D+04 ************    0.6291710  EM
3 -0.73352474D+04   98.8689891    0.0132994  EM
4 -0.71752101D+04  160.0373133    0.0218176  EM
5 -0.67671434D+04  408.0666909    0.0568717  EM
6 -0.63630291D+04  404.1143374    0.0597171  EM
7 -0.62767820D+04   86.2471501    0.0135544  EM
8 -0.62738993D+04    2.8826399    0.0004593  EM
9 -0.62738316D+04    0.0676777    0.0000108  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 17

E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
1 -0.18010562D+05    0.0000000    0.0000000  EM
2 -0.74088514D+04 ************    0.5886385  EM
3 -0.73465521D+04   62.2993194    0.0084088  EM
4 -0.72553184D+04   91.2337010    0.0124186  EM
5 -0.69220105D+04  333.3078279    0.0459398  EM
6 -0.64637046D+04  458.3058749    0.0662099  EM
7 -0.62857584D+04  177.9462329    0.0275301  EM
8 -0.62741412D+04   11.6171825    0.0018482  EM
9 -0.62738379D+04    0.3033204    0.0000483  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 18

E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
1 -0.11010618D+05    0.0000000    0.0000000  EM
2 -0.71593606D+04 3851.2574155    0.3497767  EM
3 -0.67258524D+04  433.5082237    0.0605512  EM
4 -0.63364604D+04  389.3920129    0.0578948  EM
5 -0.62757748D+04   60.6856495    0.0095772  EM
6 -0.62738784D+04    1.8963111    0.0003022  EM
7 -0.62738312D+04    0.0472704    0.0000075  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 19

E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
1 -0.15584923D+05    0.0000000    0.0000000  EM
2 -0.72557998D+04 8329.1229484    0.5344347  EM
3 -0.70569783D+04  198.8214856    0.0274017  EM
4 -0.67924050D+04  264.5732783    0.0374910  EM
5 -0.64404020D+04  352.0030312    0.0518230  EM
6 -0.62843763D+04  156.0257109    0.0242261  EM
7 -0.62741030D+04   10.2732911    0.0016347  EM
8 -0.62738366D+04    0.2664006    0.0000425  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 20

E STEP  ITER  LOGLIKELIHOOD    ABS CHANGE   REL CHANGE  ALGORITHM
1 -0.19288982D+05    0.0000000    0.0000000  EM
2 -0.69945035D+04 ************    0.6373835  EM
3 -0.63707415D+04  623.7619790    0.0891789  EM
4 -0.62754283D+04   95.3131980    0.0149611  EM
5 -0.62738505D+04    1.5778152    0.0002514  EM
6 -0.62738302D+04    0.0202994    0.0000032  EM

FINAL STAGE ITERATIONS

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 1

6 -0.62738304D+04    0.0224044    0.0000036  EM
7 -0.62738299D+04    0.0005081    0.0000001  EM
8 -0.62738299D+04    0.0000129    0.0000000  EM
9 -0.62738299D+04    0.0000003    0.0000000  EM
10 -0.62738299D+04    0.0000000    0.0000000  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 20

6 -0.62738302D+04    0.0202994    0.0000032  EM
7 -0.62738299D+04    0.0003257    0.0000001  EM
8 -0.62738299D+04    0.0000062    0.0000000  EM
9 -0.62738299D+04    0.0000001    0.0000000  EM
10 -0.62738299D+04    0.0000000    0.0000000  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 12

5 -0.62738302D+04    0.0193840    0.0000031  EM
6 -0.62738299D+04    0.0003468    0.0000001  EM
7 -0.62738299D+04    0.0000066    0.0000000  EM
8 -0.62738299D+04    0.0000001    0.0000000  EM
9 -0.62738299D+04    0.0000000    0.0000000  EM

TECHNICAL 8 OUTPUT FOR STARTING VALUE SET 15

5 -0.62738301D+04    0.0202503    0.0000032  EM
6 -0.62738299D+04    0.0002506    0.0000000  EM
7 -0.62738299D+04    0.0000036    0.0000000  EM
8 -0.62738299D+04    0.0000001    0.0000000  EM

Beginning Time:  23:13:08
Ending Time:  23:13:08
Elapsed Time:  00:00:00

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