A multistage algorithm for best-subset model selection based on the Kullback-Leibler discrepancy.
- Published in:
- Computational Statistics, 2016, v. 31, n. 2, p. 643, doi. 10.1007/s00180-015-0584-8
- By:
- Publication type:
- Article
Works matching IS 09434062 AND DT 2016 AND VI 31 AND IP 2
Results: 19
1
2
Confidence interval estimation by a joint pivot method.
- Published in:
- Computational Statistics, 2016, v. 31, n. 2, p. 497, doi. 10.1007/s00180-015-0585-7
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- Publication type:
- Article
3
A stochastic expectation-maximization algorithm for the analysis of system lifetime data with known signature.
- Published in:
- Computational Statistics, 2016, v. 31, n. 2, p. 609, doi. 10.1007/s00180-015-0586-6
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- Publication type:
- Article
4
A sequential multiple change-point detection procedure via VIF regression.
- Published in:
- Computational Statistics, 2016, v. 31, n. 2, p. 671, doi. 10.1007/s00180-015-0587-5
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- Publication type:
- Article
5
Logit tree models for discrete choice data with application to advice-seeking preferences among Chinese Christians.
- Published in:
- Computational Statistics, 2016, v. 31, n. 2, p. 799, doi. 10.1007/s00180-015-0588-4
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- Publication type:
- Article
6
Probability Distributome: a web computational infrastructure for exploring the properties, interrelations, and applications of probability distributions.
- Published in:
- Computational Statistics, 2016, v. 31, n. 2, p. 559, doi. 10.1007/s00180-015-0594-6
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- Publication type:
- Article
7
Composite likelihood and maximum likelihood methods for joint latent class modeling of disease prevalence and high-dimensional semicontinuous biomarker data.
- Published in:
- Computational Statistics, 2016, v. 31, n. 2, p. 425, doi. 10.1007/s00180-015-0597-3
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- Publication type:
- Article
8
Second-order generalized estimating equations for correlated count data.
- Published in:
- Computational Statistics, 2016, v. 31, n. 2, p. 749, doi. 10.1007/s00180-015-0599-1
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- Publication type:
- Article
9
Semiparametric variable selection for partially varying coefficient models with endogenous variables.
- Published in:
- Computational Statistics, 2016, v. 31, n. 2, p. 693, doi. 10.1007/s00180-015-0601-y
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- Publication type:
- Article
10
Introducing libeemd: a program package for performing the ensemble empirical mode decomposition.
- Published in:
- Computational Statistics, 2016, v. 31, n. 2, p. 545, doi. 10.1007/s00180-015-0603-9
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- Publication type:
- Article
11
On high-dimensional two sample mean testing statistics: a comparative study with a data adaptive choice of coefficient vector.
- Published in:
- Computational Statistics, 2016, v. 31, n. 2, p. 451, doi. 10.1007/s00180-015-0605-7
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- Publication type:
- Article
12
Correcting statistical models via empirical distribution functions.
- Published in:
- Computational Statistics, 2016, v. 31, n. 2, p. 465, doi. 10.1007/s00180-015-0607-5
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- Publication type:
- Article
13
A genetic algorithm for designing microarray experiments.
- Published in:
- Computational Statistics, 2016, v. 31, n. 2, p. 409, doi. 10.1007/s00180-015-0618-2
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- Publication type:
- Article
14
Random variate generation and connected computational issues for the Poisson-Tweedie distribution.
- Published in:
- Computational Statistics, 2016, v. 31, n. 2, p. 729, doi. 10.1007/s00180-015-0623-5
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- Publication type:
- Article
15
Improving efficiency of data augmentation algorithms using Peskun's theorem.
- Published in:
- Computational Statistics, 2016, v. 31, n. 2, p. 709, doi. 10.1007/s00180-015-0632-4
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- Publication type:
- Article
16
Boosting in Cox regression: a comparison between the likelihood-based and the model-based approaches with focus on the R-packages CoxBoost and mboost.
- Published in:
- Computational Statistics, 2016, v. 31, n. 2, p. 513, doi. 10.1007/s00180-015-0642-2
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- Publication type:
- Article
17
Density-based clustering with non-continuous data.
- Published in:
- Computational Statistics, 2016, v. 31, n. 2, p. 771, doi. 10.1007/s00180-016-0644-8
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- Publication type:
- Article
18
Comparison of Value-at-Risk models using the MCS approach.
- Published in:
- Computational Statistics, 2016, v. 31, n. 2, p. 579, doi. 10.1007/s00180-016-0646-6
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- Publication type:
- Article
19
Selectiongain: an R package for optimizing multi-stage selection.
- Published in:
- Computational Statistics, 2016, v. 31, n. 2, p. 533, doi. 10.1007/s00180-015-0583-9
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- Publication type:
- Article