Sciweavers

CSDA   2006 Dependability Computer Security
Wall of Fame | Most Viewed CSDA-2006 Paper
CSDA
2006
304views more  CSDA 2006»
14 years 17 days ago
Using principal components for estimating logistic regression with high-dimensional multicollinear data
The logistic regression model is used to predict a binary response variable in terms of a set of explicative ones. The estimation of the model parameters is not too accurate and t...
Ana M. Aguilera, Manuel Escabias, Mariano J. Valde...
Disclaimer and Copyright Notice
Sciweavers respects the rights of all copyright holders and in this regard, authors are only allowed to share a link to their preprint paper on their own website. Every contribution is associated with a desciptive image. It is the sole responsibility of the authors to ensure that their posted image is not copyright infringing. This service is compliant with IEEE copyright.
IdReadViewsTitleStatus
1Download preprint from source304
2Download preprint from source233
3Download preprint from source191
4Download preprint from source169
5Download preprint from source155
6Download preprint from source149
7Download preprint from source145
8Download preprint from source145
9Download preprint from source142
10Download preprint from source142
11Download preprint from source142
12Download preprint from source138
13Download preprint from source122
14Download preprint from source117
15Download preprint from source117
16Download preprint from source116
17Download preprint from source109
18Download preprint from source108
19Download preprint from source107
20Download preprint from source103
21Download preprint from source102
22Download preprint from source100
23Download preprint from source100
24Download preprint from source98
25Download preprint from source98
26Download preprint from source98
27Download preprint from source97
28Download preprint from source97
29Download preprint from source96
30Download preprint from source95
31Download preprint from source94
32Download preprint from source94
33Download preprint from source94
34Download preprint from source92
35Download preprint from source91
36Download preprint from source91
37Download preprint from source90
38Download preprint from source90
39Download preprint from source89
40Download preprint from source87
41Download preprint from source85
42Download preprint from source85
43Download preprint from source85
44Download preprint from source84
45Download preprint from source84
46Download preprint from source84
47Download preprint from source84
48Download preprint from source83
49Download preprint from source82
50Download preprint from source82
51Download preprint from source82
52Download preprint from source81
53Download preprint from source81
54Download preprint from source79
55Download preprint from source77
56Download preprint from source77
57Download preprint from source76
58Download preprint from source72
59Download preprint from source71
60Download preprint from source71
61Download preprint from source67
62Download preprint from source66
63Download preprint from source65
64Download preprint from source64
65Download preprint from source64
66Download preprint from source64
67Download preprint from source62
68Download preprint from source62
69Download preprint from source62
70Download preprint from source61
71Download preprint from source61
72Download preprint from source60
73Download preprint from source58
74Download preprint from source56
75Download preprint from source53
76Download preprint from source52
77Download preprint from source51
78Download preprint from source49
79Download preprint from source45
80Download preprint from source42
81Download preprint from source39