The FMM Procedure

Comparison with Roeder’s Method

It is important to note that Roeder’s original analysis proceeds in a different manner than the finite mixture modeling presented here. The technique presented by Roeder first develops a "best" range of scale parameters based on a specific criterion. Roeder then uses fixed scale parameters taken from this range to develop optimal equal-scale Gaussian mixture models.

You can reproduce Roeder’s point estimate for the density by specifying a five-component Gaussian mixture. In addition, use the EQUATE=SCALE option in the MODEL statement and a RESTRICT statement fixing the first component’s scale parameter at 0.9025 (Roeder’s h = 0.95, scale). The combination of these options produces a mixture of five Gaussian components, each with variance 0.9025. The following statements conduct this analysis:

title2 "Five Components, Equal Variances = 0.9025";
proc fmm data=galaxies;
   model v = / K=5 equate=scale;
   restrict int 0 (scale 1) = 0.9025;
run;

The output is shown in Figure 40.19 and Figure 40.20.

Figure 40.19: Reproduction of Roeder’s Five-Component Analysis of Galaxy Data

FMM Analysis of Galaxies Data
Five Components, Equal Variances = 0.9025

The FMM Procedure

Model Information
Data SetWORK.GALAXIES
Response Variablev
Type of ModelHomogeneous Mixture
DistributionNormal
Components5
Link FunctionIdentity
Estimation MethodMaximum Likelihood

Fit Statistics
-2 Log Likelihood412.2
AIC (Smaller is Better)430.2
AICC (Smaller is Better)432.7
BIC (Smaller is Better)451.9
Pearson Statistic82.5549
Effective Parameters9
Effective Components5

Linear Constraints at Solution
k = 1 Constraint
Active
Variance=0.90Yes

Parameter Estimates for Normal Model
ComponentParameterEstimateStandard
Error
z ValuePr > |z|
1Intercept26.32660.777833.85<.0001
2Intercept33.04430.548560.25<.0001
3Intercept9.71010.359127.04<.0001
4Intercept23.02950.2294100.38<.0001
5Intercept19.71870.1784110.55<.0001
1Variance0.90250  
2Variance0.90250  
3Variance0.90250  
4Variance0.90250  
5Variance0.90250  

Parameter Estimates for Mixing Probabilities
Component
Mixing
Probability
Linked Scale
GLogit(Prob)Standard
Error
z ValuePr > |z|
10.0397-2.47390.7084-3.490.0005
20.0366-2.55440.6016-4.25<.0001
30.0854-1.70710.4141-4.12<.0001
40.3678-0.24660.2699-0.910.3609
50.47060   


Figure 40.20: Density Plot for Roeder’s Analysis

 Density Plot for Roeder’s Analysis