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- Published in:
- Applied Stochastic Models in Business & Industry, 2023, v. 39, n. 3, p. 289, doi. 10.1002/asmb.2693
- Publication type:
- Article
Multivariate dynamic modeling for Bayesian forecasting of business revenue.
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- Applied Stochastic Models in Business & Industry, 2023, v. 39, n. 3, p. 292, doi. 10.1002/asmb.2704
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Discussion of "Multivariate Dynamic Modeling for Bayesian Forecasting of Business Revenue".
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- Applied Stochastic Models in Business & Industry, 2023, v. 39, n. 3, p. 310, doi. 10.1002/asmb.2725
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- Publication type:
- Article
Discussion of Bayesian forecasting of business revenue.
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- Applied Stochastic Models in Business & Industry, 2023, v. 39, n. 3, p. 312, doi. 10.1002/asmb.2741
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- Publication type:
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Discussion of "Multivariate dynamic modeling for Bayesian forecasting of business revenue".
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- Applied Stochastic Models in Business & Industry, 2023, v. 39, n. 3, p. 315, doi. 10.1002/asmb.2753
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- Publication type:
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Discussion of "Multivariate dynamic modeling for Bayesian forecasting of business revenue" by A. K. Yanchenko et al.
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- Applied Stochastic Models in Business & Industry, 2023, v. 39, n. 3, p. 318, doi. 10.1002/asmb.2746
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- Publication type:
- Article
Discussion of "Multivariate dynamic modeling for Bayesian forecasting of business revenue".
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- Applied Stochastic Models in Business & Industry, 2023, v. 39, n. 3, p. 322, doi. 10.1002/asmb.2744
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- Publication type:
- Article
Commentary on multivariate dynamic modeling for Bayesian forecasting of business revenue.
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- Applied Stochastic Models in Business & Industry, 2023, v. 39, n. 3, p. 324, doi. 10.1002/asmb.2738
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- Publication type:
- Article
Reply to Discussions of Multivariate dynamic modeling for Bayesian forecasting of business revenue.
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- Applied Stochastic Models in Business & Industry, 2023, v. 39, n. 3, p. 327, doi. 10.1002/asmb.2760
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- Publication type:
- Article
Optimal standby activation in m‐out‐of‐n systems: A preventive approach.
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- Applied Stochastic Models in Business & Industry, 2023, v. 39, n. 3, p. 333, doi. 10.1002/asmb.2740
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- Publication type:
- Article
Statistical inference for a Wiener‐based degradation model with imperfect maintenance actions under different observation schemes.
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- Applied Stochastic Models in Business & Industry, 2023, v. 39, n. 3, p. 352, doi. 10.1002/asmb.2742
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On the probability of Magnus Carlsen reaching 2900.
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- Applied Stochastic Models in Business & Industry, 2023, v. 39, n. 3, p. 372, doi. 10.1002/asmb.2745
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Micro‐level reserving for general insurance claims using a long short‐term memory network.
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- Applied Stochastic Models in Business & Industry, 2023, v. 39, n. 3, p. 382, doi. 10.1002/asmb.2750
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- Publication type:
- Article
Time series model for GLWB with surrender benefit and stochastic interest rate: Dynamic withdrawal approach.
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- Applied Stochastic Models in Business & Industry, 2023, v. 39, n. 3, p. 408, doi. 10.1002/asmb.2751
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- Publication type:
- Article
Order restricted inference for a multiple step‐stress model with long‐term survivors for a general family of distributions.
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- Applied Stochastic Models in Business & Industry, 2023, v. 39, n. 3, p. 426, doi. 10.1002/asmb.2754
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- Article
Deep learning models for inflation forecasting.
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- Applied Stochastic Models in Business & Industry, 2023, v. 39, n. 3, p. 447, doi. 10.1002/asmb.2757
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- Publication type:
- Article
A review of Bayesian dynamic forecasting models: Applications in marketing.
- Published in:
- Applied Stochastic Models in Business & Industry, 2023, v. 39, n. 3, p. 471, doi. 10.1002/asmb.2756
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- Article