Skip to content

R Package: mmlcr and/or flexmix

2 messages · Geller, Scott (IHG), Friedrich Leisch

Geller, Scott (IHG)
# 
Greetings 

 

I'm a relatively new R user and I'm trying to build a latent class model.
I've used the 'R Site Search' and it appears there's not much dialogue on
these packages

 

On mmlcr, I've gotten it working, but not sure if I'm using it correctly.

 

On flexmix, I can only seem to get results for one class. 

 

I'm attaching my code below - if anyone is familiar with either of these
packages, I'd really appreciate some assistance or direction.  I'm also
attaching a small sample dataset.

 

Many thanks for your help!

 

Scott Geller

 

 

library(mmlcr)

 

model2 = mmlcr(outer = ~ first_brand_HOLIDAY + perc_zone1 +
perc_Group_nights + perc_num_asian + DaysBetweenStays + CROStays +
DaysSinceLastStay + wghtmean_median_age_pop100 + perc_num_white +
perc_num_hispanic + perc_CROStays + numMonthsActive + WEBStays +
property_loyalty + perc_NoZone + ltgold1 + ltgold3  + rho + p_hat_PCR|
gst_id, components = list(list(formula = nts ~ PCR_Dummy_class, class =
"poislong")),data=Dataset, n.groups = 5, max.iter = 5000)

 

 

libray(flexmix)

 

m1<-flexmix(nts ~ first_brand_HOLIDAY+ perc_zone1+ perc_Group_nights+
perc_num_asian+  DaysBetweenStays+ CROStays+ DaysSinceLastStay+
wghtmean_median_age_pop100+ perc_num_white+ perc_num_hispanic+
perc_CROStays+ numMonthsActive+ WEBStays+ property_loyalty+ perc_NoZone+
rho+ PCR_Dummy_class+ ltgold1+ ltgold3+ p_hat_PCR, data = data, k = 2, model
= FLXglm(family = "poisson"))

 

rm1<-refit(m1)

summary(rm1)

 

 

 

Scott Geller

Advanced Analytics,

Decision Sciences Department,

InterContinental Hotels Group

 

770-604-5149
Friedrich Leisch
# 
> Greetings 
  > I'm a relatively new R user and I'm trying to build a latent class model.
  > I've used the 'R Site Search' and it appears there's not much dialogue on
  > these packages

[...]


  > libray(flexmix)

  > m1<-flexmix(nts ~ first_brand_HOLIDAY+ perc_zone1+ perc_Group_nights+
  > perc_num_asian+  DaysBetweenStays+ CROStays+ DaysSinceLastStay+
  > wghtmean_median_age_pop100+ perc_num_white+ perc_num_hispanic+
  > perc_CROStays+ numMonthsActive+ WEBStays+ property_loyalty+ perc_NoZone+
  > rho+ PCR_Dummy_class+ ltgold1+ ltgold3+ p_hat_PCR, data = data, k = 2, model
  > = FLXglm(family = "poisson"))

  > rm1<-refit(m1)

  > summary(rm1)

 

[ Scott sent me in private a subset of the data ]

For me this seems to work fine:

R> set.seed(123)
R> m1<-flexmix(nts ~ first_brand_HOLIDAY+ perc_zone1+ perc_Group_nights+
+ perc_num_asian+  DaysBetweenStays+ CROStays+ DaysSinceLastStay+
+ wghtmean_median_age_pop100+ perc_num_white+ perc_num_hispanic+
+ perc_CROStays+ numMonthsActive+ WEBStays+ property_loyalty+ perc_NoZone+
+ rho+ PCR_Dummy_class+ ltgold1+ ltgold3+ p_hat_PCR, data = data, k = 2, model
+ = FLXglm(family = "poisson"))
R> m1

Call:
flexmix(formula = nts ~ first_brand_HOLIDAY + perc_zone1 + perc_Group_nights +
    perc_num_asian + DaysBetweenStays + CROStays + DaysSinceLastStay +
    wghtmean_median_age_pop100 + perc_num_white + perc_num_hispanic +
    perc_CROStays + numMonthsActive + WEBStays + property_loyalty +
    perc_NoZone + rho + PCR_Dummy_class + ltgold1 + ltgold3 +
    p_hat_PCR, data = data, k = 2, model = FLXglm(family = "poisson"))

Cluster sizes:
  1   2
 93 906

convergence after 49 iterations


R> rm1<-refit(m1)
R>
R> summary(rm1)

Call:
refit(m1)

Component 1 :
                              Estimate  Std. Error z value  Pr(>|z|)
(Intercept)                 1.0108e+00  6.4399e-01  1.5696 0.1164971
first_brand_HOLIDAY        -9.3504e-01  4.6151e-01 -2.0261 0.0427594
perc_zone1                  1.3936e-01  7.4383e-01  0.1874 0.8513845
...

-------------
Component 2 :
                              Estimate  Std. Error z value  Pr(>|z|)
(Intercept)                 1.00799714  0.39133294  2.5758   0.01000
first_brand_HOLIDAY        -0.07928984  0.15935997 -0.4976   0.61880
perc_zone1                  0.01208886  0.42596711  0.0284   0.97736
...


So I cannot reproduce the problem. Is maybo one cluster in your
solution empty? The EM algorithm can end up in a local optimum with
one cluster empty ... either run flexmix() several times by hand or
use stepFlexmix() to do so automatically.

HTH,