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2006

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Using principal components for estimating logistic regression with high-dimensional multicollinear data

13 years 11 months ago

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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...

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Id	Views	Title	Status

1	304	Using principal components for estimating logistic regression with high-dimensional multicollinear data	claim
2	233	Analysis of Type-II progressively hybrid censored data	claim
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4	169	Generalized structured additive regression based on Bayesian P-splines	claim
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7	145	Improved predictions penalizing both slope and curvature in additive models	claim
8	145	An improved method for generalized constrained canonical correlation analysis	claim
9	142	A studentized range test for the equivalency of normal means under heteroscedasticity	claim
10	142	Automatic approximation of the marginal likelihood in non-Gaussian hierarchical models	claim
11	142	A Bayesian approach to bandwidth selection for multivariate kernel density estimation	claim
12	138	Automatic dimensionality selection from the scree plot via the use of profile likelihood	claim
13	122	The fuzzy approach to statistical analysis	claim
14	117	GACV for quantile smoothing splines	claim
15	117	Exact maximum likelihood estimation of structured or unit root multivariate time series models	claim
16	116	Bayesian multiscale analysis for time series data	claim
17	109	Possibility theory and statistical reasoning	claim
18	108	Repeated median and hybrid filters	claim
19	107	Optimal confidence interval for the largest normal mean under heteroscedasticity	claim
20	103	LASS: a tool for the local analysis of self-similarity	claim
21	102	An improved Akaike information criterion for state-space model selection	claim
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29	96	Analysis of new variable selection methods for discriminant analysis	claim
30	95	Identifying influential multinomial observations by perturbation	claim
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32	94	The nature of sensitivity in monotone missing not at random models	claim
33	94	Signal extraction for simulated games with a large number of players	claim
34	92	Robust measures of tail weight	claim
35	91	Model-based cluster and discriminant analysis with the MIXMOD software	claim
36	91	Maximum a posteriori pruning on decision trees and its application to bootstrap BUMPing	claim
37	90	Comparing two binary diagnostic tests in the presence of verification bias	claim
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39	89	Multivariate time series modeling and classification via hierarchical VAR mixtures	claim
40	87	Choice of B-splines with free parameters in the flexible discriminant analysis context	claim
41	85	Detecting change-points in multidimensional stochastic processes	claim
42	85	Fast and compact smoothing on large multidimensional grids	claim
43	85	Two-way Poisson mixture models for simultaneous document classification and word clustering	claim
44	84	Extremal financial risk models and portfolio evaluation	claim
45	84	Three-mode partitioning	claim
46	84	Performing hypothesis tests on the shape of functional data	claim
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48	83	Linear grouping using orthogonal regression	claim
49	82	2nd Special issue on matrix computations and statistics	claim
50	82	Multivariate distribution models with generalized hyperbolic margins	claim
51	82	Nearest neighbours in least-squares data imputation algorithms with different missing patterns	claim
52	81	Flexible temporal expression profile modelling using the Gaussian process	claim
53	81	A recursive approach to detect multivariable conditional variance components and conditional random effects	claim
54	79	Nonlinear dynamics in Nasdaq dealer quotes	claim
55	77	Hierarchical Bayesian modelling of spatial age-dependent mortality	claim
56	77	Econometric methods of signal extraction	claim
57	76	Mean estimation with calibration techniques in presence of missing data	claim
58	72	Generalized theory of uncertainty (GTU) - principal concepts and ideas	claim
59	71	Practical representations of incomplete probabilistic knowledge	claim
60	71	Computation of Huber's M-estimates for a block-angular regression problem	claim
61	67	Sensitivity analysis of the strain criterion for multidimensional scaling	claim
62	66	A dynamic model of expected bond returns: A functional gradient descent approach	claim
63	65	Dimension reduction in functional regression with applications	claim
64	64	Time-frequency analysis - G	claim
65	64	Semiparametric estimation in perturbed long memory series	claim
66	64	Segmenting magnetic resonance images via hierarchical mixture modelling	claim
67	62	Wavelet-based bootstrapping of spatial patterns on a finite lattice	claim
68	62	Nonparametric density estimation and clustering in astronomical sky surveys	claim
69	62	Introduction to the special issue on statistical signal extraction and filtering	claim
70	61	An atmosphere-ocean time series model of global climate change	claim
71	61	Finding a causal ordering via independent component analysis	claim
72	60	Numerical integration in logistic-normal models	claim
73	58	Bayesian model choice based on Monte Carlo estimates of posterior model probabilities	claim
74	56	Iterated importance sampling in missing data problems	claim
75	53	Testing the martingale difference hypothesis using integrated regression functions	claim
76	52	Univariate statistical analysis with fuzzy data	claim
77	51	Robust estimation of dimension reduction space	claim
78	49	An iterated parametric approach to nonstationary signal extraction	claim
79	45	Estimation of quantile mixtures via L-moments and trimmed L-moments	claim
80	42	Time series clustering based on forecast densities	claim
81	39	A major improvement to the Network Algorithm for Fisher's Exact Test in 2×c	claim

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