References in zbMATH (referenced in 19 articles , 2 standard articles )

Showing results 1 to 19 of 19.
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  1. Hunter, Michael D.; Fatimah, Haya; Bornovalova, Marina A.: Two filtering methods of forecasting linear and nonlinear dynamics of intensive longitudinal data (2022)
  2. Li, Yanling; Oravecz, Zita; Zhou, Shuai; Bodovski, Yosef; Barnett, Ian J.; Chi, Guangqing; Zhou, Yuan; Friedman, Naomi P.; Vrieze, Scott I.; Chow, Sy-Miin: Bayesian forecasting with a regime-switching zero-inflated multilevel Poisson regression model: an application to adolescent alcohol use with spatial covariates (2022)
  3. Tucker S. McElroy, James A. Livsey: Ecce Signum: An R Package for Multivariate Signal Extraction and Time Series Analysis (2022) arXiv
  4. Benjamin Christoffersen: dynamichazard: Dynamic Hazard Models Using State Space Models (2021) not zbMATH
  5. Michaud, N., de Valpine, P., Turek, D., Paciorek, C. J., Nguyen, D.: Sequential Monte Carlo Methods in the nimble and nimbleSMC R Packages (2021) not zbMATH
  6. Ning Ning, Jinwen Qiu: The mbsts package: Multivariate Bayesian Structural Time Series Models in R (2021) arXiv
  7. Peder Bacher, Hjörleifur G. Bergsteinsson, Linde Frölke, Mikkel L. Sørensen, Julian Lemos-Vinasco, Jon Liisberg, Jan Kloppenborg Møller, Henrik Aalborg Nielsen, Henrik Madsen: onlineforecast: An R package for adaptive and recursive forecasting (2021) arXiv
  8. Sogandi, Fatemeh; Aminnayeri, Majid; Mohammadpour, Adel; Amiri, Amirhossein: Phase I risk-adjusted Bernoulli chart in multistage healthcare processes based on the state-space model (2021)
  9. Antonio Calcagnì, Massimiliano Pastore, Gianmarco Altoè: ssMousetrack: Analysing computerized tracking data via Bayesian state-space models in R (2019) arXiv
  10. Binkowski, Karol; He, Peilun; Kordzakhia, Nino; Shevchenko, Pavel: On the parameter estimation in the Schwartz-Smith’s two-factor model (2019)
  11. Goin, Dana E.; Ahern, Jennifer: Identification of spikes in time series (2019)
  12. Raphael Saavedra, Guilherme Bodin, Mario Souto: StateSpaceModels.jl: a Julia Package for Time-Series Analysis in a State-Space Framework (2019) arXiv
  13. Marco Villegas; Diego Pedregal: SSpace: A Toolbox for State Space Modeling (2018) not zbMATH
  14. Jouni Helske: KFAS: Exponential Family State Space Models in R (2017) not zbMATH
  15. Tobias Liboschik; Konstantinos Fokianos; Roland Fried: tscount: An R Package for Analysis of Count Time Series Following Generalized Linear Models (2017) not zbMATH
  16. Helske, Jouni: Prediction and interpolation of time series by state space models (2015)
  17. Ruiz-Cárdenas, Ramiro; Krainski, Elias T.; Rue, Håvard: Direct fitting of dynamic models using integrated nested Laplace approximations -- INLA (2012)
  18. Fernando Tusell: Kalman Filtering in R (2011) not zbMATH
  19. Giovanni Petris; Sonia Petrone: State Space Models in R (2011) not zbMATH