Adaptive and robust experimental design for linear dynamical models using Kalman filter
Author
Abstract
Suggested Citation
DOI: 10.1007/s00362-023-01438-9
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Rong Chen & Jun S. Liu, 2000. "Mixture Kalman filters," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(3), pages 493-508.
- Jian He & Asma Khedher & Peter Spreij, 2021. "A Kalman particle filter for online parameter estimation with applications to affine models," Statistical Inference for Stochastic Processes, Springer, vol. 24(2), pages 353-403, July.
- Elizabeth G. Ryan & Christopher C. Drovandi & James M. McGree & Anthony N. Pettitt, 2016. "A Review of Modern Computational Algorithms for Bayesian Optimal Design," International Statistical Review, International Statistical Institute, vol. 84(1), pages 128-154, April.
- Cavanaugh, Joseph E. & Shumway, Robert H., 1996. "On computing the expected Fisher information matrix for state-space model parameters," Statistics & Probability Letters, Elsevier, vol. 26(4), pages 347-355, March.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Andrea Beccarini, 2024. "Testing omitted variables in VARs," Statistical Papers, Springer, vol. 65(5), pages 3093-3109, July.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Tobias Hartl & Roland Jucknewitz, 2022.
"Approximate state space modelling of unobserved fractional components,"
Econometric Reviews, Taylor & Francis Journals, vol. 41(1), pages 75-98, January.
- Tobias Hartl & Roland Weigand, 2018. "Approximate State Space Modelling of Unobserved Fractional Components," Papers 1812.09142, arXiv.org, revised May 2020.
- Leif Anders Thorsrud, 2016. "Nowcasting using news topics. Big Data versus big bank," Working Paper 2016/20, Norges Bank.
- Mengheng Li & Siem Jan (S.J.) Koopman, 2018. "Unobserved Components with Stochastic Volatility in U.S. Inflation: Estimation and Signal Extraction," Tinbergen Institute Discussion Papers 18-027/III, Tinbergen Institute.
- Alexander Tsyplakov, 2011. "An introduction to state space modeling (in Russian)," Quantile, Quantile, issue 9, pages 1-24, July.
- James M. Nason & Gregor W. Smith, 2021.
"Measuring the slowly evolving trend in US inflation with professional forecasts,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(1), pages 1-17, January.
- James M. Nason & Gregor W. Smith, 2013. "Measuring The Slowly Evolving Trend In Us Inflation With Professional Forecasts," Working Paper 1316, Economics Department, Queen's University.
- James M. Nason & Gregor W. Smith, 2014. "Measuring the Slowly Evolving Trend in US Inflation with Professional Forecasts," CAMA Working Papers 2014-07, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Koop, Gary & Korobilis, Dimitris, 2011.
"UK macroeconomic forecasting with many predictors: Which models forecast best and when do they do so?,"
Economic Modelling, Elsevier, vol. 28(5), pages 2307-2318, September.
- Koop, Gary & Korobilis, Dimitris, 2009. "UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?," SIRE Discussion Papers 2009-40, Scottish Institute for Research in Economics (SIRE).
- Gary Koop & Dimitris Korobilis, 2011. "UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?," Working Papers 1118, University of Strathclyde Business School, Department of Economics.
- Gary Koop & Dimitris Korompilis, 2009. "UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?," Working Papers 0917, University of Strathclyde Business School, Department of Economics.
- Koop, Gary & Korobilis, Dimitris, 2011. "UK Macroeconomic Forecasting with Many Predictors: Which Models Forecast Best and When Do They Do So?," SIRE Discussion Papers 2011-39, Scottish Institute for Research in Economics (SIRE).
- David J Price & Alexandre Breuzé & Richard Dybowski & Piero Mastroeni & Olivier Restif, 2017. "An efficient moments-based inference method for within-host bacterial infection dynamics," PLOS Computational Biology, Public Library of Science, vol. 13(11), pages 1-27, November.
- Siddhartha Chib & Minchul Shin & Fei Tan, 2023.
"DSGE-SVt: An Econometric Toolkit for High-Dimensional DSGE Models with SV and t Errors,"
Computational Economics, Springer;Society for Computational Economics, vol. 61(1), pages 69-111, January.
- Siddhartha Chib & Minchul Shin & Fei Tan, 2021. "DSGE-SVt: An Econometric Toolkit for High-Dimensional DSGE Models with SV and t Errors," Working Papers 21-02, Federal Reserve Bank of Philadelphia.
- Ng'ombe, John, 2019. "Economics of the Greenseeder Hand Planter, Discrete Choice Modeling, and On-Farm Field Experimentation," Thesis Commons jckt7, Center for Open Science.
- Mengheng Li & Siem Jan Koopman, 2021. "Unobserved components with stochastic volatility: Simulation‐based estimation and signal extraction," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 614-627, August.
- Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021.
"Factor extraction using Kalman filter and smoothing: This is not just another survey,"
International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
- Poncela Blanco, Maria Pilar, 2020. "Factor extraction using Kalman filter and smoothing: this is not just another survey," DES - Working Papers. Statistics and Econometrics. WS 30644, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Karamé, Frédéric, 2018.
"A new particle filtering approach to estimate stochastic volatility models with Markov-switching,"
Econometrics and Statistics, Elsevier, vol. 8(C), pages 204-230.
- Frédéric Karamé, 2018. "A new particle filtering approach to estimate stochastic volatility models with Markov-switching," Post-Print hal-02296093, HAL.
- Anyosa, Susan & Eidsvik, Jo & Pizarro, Oscar, 2023. "Adaptive spatial designs minimizing the integrated Bernoulli variance in spatial logistic regression models - with an application to benthic habitat mapping," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
- Giampiero Marra & Rosalba Radice & Silvia Missiroli, 2014. "Testing the hypothesis of absence of unobserved confounding in semiparametric bivariate probit models," Computational Statistics, Springer, vol. 29(3), pages 715-741, June.
- Dacheng Liu & Tao Lu & Xu-Feng Niu & Hulin Wu, 2011. "Mixed-Effects State-Space Models for Analysis of Longitudinal Dynamic Systems," Biometrics, The International Biometric Society, vol. 67(2), pages 476-485, June.
- Dehideniya, Mahasen B. & Drovandi, Christopher C. & McGree, James M., 2018. "Optimal Bayesian design for discriminating between models with intractable likelihoods in epidemiology," Computational Statistics & Data Analysis, Elsevier, vol. 124(C), pages 277-297.
- Nicolas Chopin, 2007. "Dynamic Detection of Change Points in Long Time Series," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 59(2), pages 349-366, June.
- Drew Creal & Siem Jan Koopman & Eric Zivot, 2010.
"Extracting a robust US business cycle using a time-varying multivariate model-based bandpass filter,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 25(4), pages 695-719.
- Drew Creal & Siem Jan Koopman & Eric Zivot, 2008. "Extracting a Robust U.S. Business Cycle Using a Time-Varying Multivariate Model-Based Bandpass Filter," Working Papers UWEC-2008-15-FC, University of Washington, Department of Economics.
- Benjamin K. Johannsen & Elmar Mertens, 2021.
"A Time‐Series Model of Interest Rates with the Effective Lower Bound,"
Journal of Money, Credit and Banking, Blackwell Publishing, vol. 53(5), pages 1005-1046, August.
- Benjamin K. Johannsen & Elmar Mertens, 2016. "A Time Series Model of Interest Rates With the Effective Lower Bound," Finance and Economics Discussion Series 2016-033, Board of Governors of the Federal Reserve System (U.S.).
- Benjamin K Johannsen & Elmar Mertens, 2018. "A time series model of interest rates with the effective lower bound," BIS Working Papers 715, Bank for International Settlements.
- Rimstad, Kjartan & Omre, Henning, 2013. "Approximate posterior distributions for convolutional two-level hidden Markov models," Computational Statistics & Data Analysis, Elsevier, vol. 58(C), pages 187-200.
More about this item
Keywords
Optimal experimental design; Bayesian experimental design; Adaptive experimental design; Dynamical system; Kalman filter;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:stpapr:v:64:y:2023:i:4:d:10.1007_s00362-023-01438-9. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.