Works matching IS 09434062 AND DT 2019 AND VI 34 AND IP 1
Results: 19
Neural network gradient Hamiltonian Monte Carlo.
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- Computational Statistics, 2019, v. 34, n. 1, p. 281, doi. 10.1007/s00180-018-00861-z
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Assessing variable importance in clustering: a new method based on unsupervised binary decision trees.
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- Computational Statistics, 2019, v. 34, n. 1, p. 301, doi. 10.1007/s00180-018-0857-0
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Flexible regression modeling for censored data based on mixtures of student-t distributions.
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- Computational Statistics, 2019, v. 34, n. 1, p. 123, doi. 10.1007/s00180-018-0856-1
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Improved model-based clustering performance using Bayesian initialization averaging.
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- Computational Statistics, 2019, v. 34, n. 1, p. 201, doi. 10.1007/s00180-018-0855-2
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Improving the prediction performance of the LASSO by subtracting the additive structural noises.
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- Computational Statistics, 2019, v. 34, n. 1, p. 415, doi. 10.1007/s00180-018-0849-0
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Bayesian analysis of Weibull distribution based on progressive type-II censored competing risks data with binomial removals.
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- Computational Statistics, 2019, v. 34, n. 1, p. 233, doi. 10.1007/s00180-018-0847-2
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A homoscedasticity test for the accelerated failure time model.
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- Computational Statistics, 2019, v. 34, n. 1, p. 433, doi. 10.1007/s00180-018-0840-9
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Estimating reducible stochastic differential equations by conversion to a least-squares problem.
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- Computational Statistics, 2019, v. 34, n. 1, p. 23, doi. 10.1007/s00180-018-0837-4
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Shape mixtures of skew-t-normal distributions: characterizations and estimation.
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- Computational Statistics, 2019, v. 34, n. 1, p. 323, doi. 10.1007/s00180-018-0835-6
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Pseudo-Bayesian D-optimal designs for longitudinal Poisson mixed models with correlated errors.
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- Computational Statistics, 2019, v. 34, n. 1, p. 71, doi. 10.1007/s00180-018-0834-7
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Approximate Bayesian computation for Lorenz curves from grouped data.
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- Computational Statistics, 2019, v. 34, n. 1, p. 253, doi. 10.1007/s00180-018-0831-x
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Bootstrapping estimates of stability for clusters, observations and model selection.
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- Computational Statistics, 2019, v. 34, n. 1, p. 349, doi. 10.1007/s00180-018-0830-y
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SamP2CeT: an interactive computer program for sample size and power calculation for two-level cost-effectiveness trials.
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- Computational Statistics, 2019, v. 34, n. 1, p. 47, doi. 10.1007/s00180-018-0829-4
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Joint modelling of two count variables when one of them can be degenerate.
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- Computational Statistics, 2019, v. 34, n. 1, p. 153, doi. 10.1007/s00180-018-0828-5
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Fusion learning algorithm to combine partially heterogeneous Cox models.
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- Computational Statistics, 2019, v. 34, n. 1, p. 395, doi. 10.1007/s00180-018-0827-6
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An iterative algorithm to bound partial moments.
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- Computational Statistics, 2019, v. 34, n. 1, p. 89, doi. 10.1007/s00180-018-0825-8
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Modified beta modified-Weibull distribution.
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- Computational Statistics, 2019, v. 34, n. 1, p. 173, doi. 10.1007/s00180-018-0822-y
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An extension of the K-means algorithm to clustering skewed data.
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- Computational Statistics, 2019, v. 34, n. 1, p. 373, doi. 10.1007/s00180-018-0821-z
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The performance of latent growth curve model-based structural equation model trees to uncover population heterogeneity in growth trajectories.
- Published in:
- Computational Statistics, 2019, v. 34, n. 1, p. 1, doi. 10.1007/s00180-018-0815-x
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- Article