A nonparametric random coefficient approach for life expectancy growth using a hierarchical mixture likelihood model with application to regional data from North Rhine-Westphalia (Germany)

Table 4 Maximum posterior classification (MAP) for men, J = 7

Region	Name	Class	e _.1	e _.2	e _.3	e _.4	e _.5	e _.6	e _.7
1	Düsseldorf	2	0	0.95	0.05	0	0	0	0
2	Duisburg	1	1	0	0	0	0	0	0
3	Essen	2	0	1	0	0	0	0	0
4	Krefeld	4	0	0	0	1	0	0	0
5	Mönchengladbach	2	0	1	0	0	0	0	0
6	Mülheim a.d. Ruhr	4	0	0	0.01	0.99	0	0	0
7	Oberhausen	1	1	0	0	0	0	0	0
8	Remscheid	2	0	1	0	0	0	0	0
9	Solingen	4	0	0	0	1	0	0	0
10	Wuppertal	3	0	0	1	0	0	0	0
11	Kleve	3	0	0	1	0	0	0	0
12	Mettmann	6	0	0	0	0	0.03	0.97	0
13	Neuss	6	0	0	0	0	0.01	0.99	0
14	Viersen	4	0	0	0	1	0	0	0
15	Wesel	4	0	0	0	1	0	0	0
16	Aachen (city)	6	0	0	0	0	0	1	0
17	Bonn	7	0	0	0	0	0	0	1
18	Köln	4	0	0	0.03	0.97	0	0	0
19	Leverkusen	5	0	0	0	0	1	0	0
20	Aachen (rural)	4	0	0	0.16	0.84	0	0	0
21	Düren	4	0	0	0	1	0	0	0
22	Erftkreis	5	0	0	0	0	1	0	0
23	Euskirchen	3	0	0	1	0	0	0	0
24	Heinsberg	4	0	0	0	1	0	0	0
25	Oberbergischer Kreis	4	0	0	0	1	0	0	0
26	Rheinisch-Bergischer Kreis	7	0	0	0	0	0	0	1
27	Rhein-Sieg-Kreis	7	0	0	0	0	0	0	1
28	Bottrop	2	0	1	0	0	0	0	0
29	Gelsenkirchen	1	1	0	0	0	0	0	0
30	Münster	7	0	0	0	0	0	0	1
31	Borken	4	0	0	0	0.96	0.04	0	0
32	Coesfeld	6	0	0	0	0	0.14	0.86	0
33	Recklinghausen	2	0	1	0	0	0	0	0
34	Steinfurt	5	0	0	0	0	1	0	0
35	Warendorf	5	0	0	0	0	0.96	0.04	0
36	Bielefeld	5	0	0	0	0	1	0	0
37	Gütersloh	6	0	0	0	0	0	1	0
38	Herford	5	0	0	0	0	1	0	0
39	Höxter	5	0	0	0	0	0.99	0.01	0
40	Lippe	5	0	0	0	0	0.92	0.08	0
41	Minden-Lübbecke	4	0	0	0.01	0.99	0	0	0
42	Paderborn	5	0	0	0	0	1	0	0
43	Bochum	2	0	1	0	0	0	0	0
44	Dortmund	2	0	1	0	0	0	0	0
45	Hagen	2	0	1	0	0	0	0	0
46	Hamm	3	0	0	1	0	0	0	0
47	Herne	2	0	1	0	0	0	0	0
48	Ennepe-Ruhr-Kreis	3	0	0	1	0	0	0	0
49	Hochsauerlandkreis	4	0	0	0	0.88	0.12	0	0
50	Märkischer Kreis	3	0	0	1	0	0	0	0
51	Olpe	4	0	0	0	1	0	0	0
52	Siegen-Wittgenstein	4	0	0	0	1	0	0	0
53	Soest	3	0	0	1	0	0	0	0
54	Unna	3	0	0	0.99	0.01	0	0	0

ISSN: 1471-2288