Dear useRs:
I successfully model-based partitioned several datasets through the use of
mob from the party package (thanks Achim et al. once again !!!). At times,
however, the partitioning leads to terminal nodes in which the parameter
estimates of the model are not significant (although the split points and in
general the proposed segmentation both seem reasonable). As I do not seem
to be able to come up with an intuitive explanation/interpretation for this
(other than that the partitioning model may be appropriate for parts of the
dataset(s)), I wonder if any of you could share your thoughts on this topic
with me. For your convenience I attached a relevant set of results below.
My system: Windowd XP, R 2.11.1, party version 0.9-9997.
Thanks.
Tudor
$`2`
Call:
NULL
Deviance Residuals:
Min 1Q Median
3Q Max
-2.1613499829328759 -0.1182099512510448 0.0000000000000000
0.1199438072333263 1.7963628663418680
Coefficients:
Estimate Std. Error z value
Pr(>|z|)
(Intercept) 38.6736721222665096 5.1182299436934375 7.55606
0.000000000000041545 ***
P -3.8195232976021787 0.5042297985419135 -7.57497
0.000000000000035922 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 407.0806101624161 on 293 degrees of freedom
Residual deviance: 132.0087256781199 on 292 degrees of freedom
AIC: 136.0087256781199
Number of Fisher Scoring iterations: 7
$`3`
Call:
NULL
Deviance Residuals:
Min 1Q Median
3Q Max
-0.00009134433923085110 0.00000000000000000000 0.00000000000000000000
0.00000000000000000000 0.00009204763394325872
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 1755.7555999083327 601505.6700290179579 0.00292 0.99767
P -181.3394660743267 62127.5207770660636 -0.00292 0.99767
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 94.20918454290385568583588 on 67 degrees of freedom
Residual deviance: 0.00000001683616309495537 on 66 degrees of freedom
AIC: 4.000000016836163
Number of Fisher Scoring iterations: 25
--
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