Works matching IS 00203157 AND DT 2020 AND VI 72 AND IP 1
Results: 14
Reply to Discussion of "Bayesian forecasting of multivariate time series: scalability, structure uncertainty and decisions".
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- Annals of the Institute of Statistical Mathematics, 2020, v. 72, n. 1, p. 41, doi. 10.1007/s10463-019-00744-0
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Discussion of "Bayesian forecasting of multivariate time series: scalability, structure uncertainty and decisions".
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- Annals of the Institute of Statistical Mathematics, 2020, v. 72, n. 1, p. 37, doi. 10.1007/s10463-019-00743-1
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- Article
Discussion of "Bayesian forecasting of multivariate time series: scalability, structure uncertainty and decisions".
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- Annals of the Institute of Statistical Mathematics, 2020, v. 72, n. 1, p. 33, doi. 10.1007/s10463-019-00742-2
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Bayesian forecasting of multivariate time series: scalability, structure uncertainty and decisions.
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- Annals of the Institute of Statistical Mathematics, 2020, v. 72, n. 1, p. 1, doi. 10.1007/s10463-019-00741-3
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Asymptotic theory of the adaptive Sparse Group Lasso.
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- Annals of the Institute of Statistical Mathematics, 2020, v. 72, n. 1, p. 297, doi. 10.1007/s10463-018-0692-7
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Sequential fixed accuracy estimation for nonstationary autoregressive processes.
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- Annals of the Institute of Statistical Mathematics, 2020, v. 72, n. 1, p. 235, doi. 10.1007/s10463-018-0689-2
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Semiparametric quantile regression with random censoring.
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- Annals of the Institute of Statistical Mathematics, 2020, v. 72, n. 1, p. 265, doi. 10.1007/s10463-018-0688-3
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A two-stage sequential conditional selection approach to sparse high-dimensional multivariate regression models.
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- Annals of the Institute of Statistical Mathematics, 2020, v. 72, n. 1, p. 65, doi. 10.1007/s10463-018-0686-5
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New kernel estimators of the hazard ratio and their asymptotic properties.
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- Annals of the Institute of Statistical Mathematics, 2020, v. 72, n. 1, p. 187, doi. 10.1007/s10463-018-0685-6
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Estimating quantiles in imperfect simulation models using conditional density estimation.
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- Annals of the Institute of Statistical Mathematics, 2020, v. 72, n. 1, p. 123, doi. 10.1007/s10463-018-0683-8
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Discovering model structure for partially linear models.
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- Annals of the Institute of Statistical Mathematics, 2020, v. 72, n. 1, p. 45, doi. 10.1007/s10463-018-0682-9
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An empirical likelihood approach under cluster sampling with missing observations.
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- Annals of the Institute of Statistical Mathematics, 2020, v. 72, n. 1, p. 91, doi. 10.1007/s10463-018-0681-x
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Inference on a distribution function from ranked set samples.
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- Annals of the Institute of Statistical Mathematics, 2020, v. 72, n. 1, p. 157, doi. 10.1007/s10463-018-0680-y
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Marginal quantile regression for varying coefficient models with longitudinal data.
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- Annals of the Institute of Statistical Mathematics, 2020, v. 72, n. 1, p. 213, doi. 10.1007/s10463-018-0684-7
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