Bibliographies thématiques / Multivariate filter

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Littérature scientifique sur le sujet « Multivariate filter »

Auteur : Grafiati
Publié le 9 mars 2023
Mis à jour le 31 juillet 2025

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Articles de revues sur le sujet "Multivariate filter"

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Spangl, Bernhard. "Robust Filtering for Linear State-space Models with Non-propagating Outliers Following a Mixture of Gaussian Distributions." Austrian Journal of Statistics 54, no. 3 (2025): 150–68. https://doi.org/10.17713/ajs.v54i3.2077.

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The problem of recursive filtering in linear state-space models is considered. The solution to this problem is the classical Kalman filter which is optimal in the sense that it minimizes the variance of the estimated states, if the error processes of the state and observation equations are both Gaussian. However, the Kalman filter is well known to be sensitive to outliers, so robustness is an issue. Two approximate conditional-mean (ACM) type filters for vector-valued observations are proposed that generalize existing univariate filters of similar type to the multivariate case.These new ACM-ty
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WHITCHER, BRANDON, and PETER F. CRAIGMILE. "MULTIVARIATE SPECTRAL ANALYSIS USING HILBERT WAVELET PAIRS." International Journal of Wavelets, Multiresolution and Information Processing 02, no. 04 (2004): 567–87. http://dx.doi.org/10.1142/s0219691304000652.

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We investigate the use of Hilbert wavelet pairs (HWPs) in the non-decimated discrete wavelet transform for the time-varying spectral analysis of multivariate time series. HWPs consist of two high-pass and two low-pass compactly supported filters, such that one high-pass filter is the Hilbert transform (approximately) of the other. Thus, common quantities in the spectral analysis of time series (e.g., power spectrum, coherence, phase) may be estimated in both time and frequency. Compact support of the wavelet filters ensures that the frequency axis will be partitioned dyadically as with the usu
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Vitek, Francis. "A Closed Form Multivariate Linear Filter." IMF Working Papers 18, no. 275 (2018): 1. http://dx.doi.org/10.5089/9781484388785.001.

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Chen, Qiuhui, Charles A. Micchelli, Silong Peng, and Yuesheng Xu. "Multivariate Filter Banks Having Matrix Factorizations." SIAM Journal on Matrix Analysis and Applications 25, no. 2 (2003): 517–31. http://dx.doi.org/10.1137/s0895479802412735.

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García Infante, Juan Carlos, José de J. Medel Juárez, and Juan Carlos Sánchez García. "Neural fuzzy digital filtering: multivariate identifier filters involving multiple inputs and multiple outputs (MIMO)." Ingeniería e Investigación 31, no. 1 (2011): 184–92. http://dx.doi.org/10.15446/ing.investig.v31n1.20569.

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Multivariate identifier filters (multiple inputs and multiple outputs - MIMO) are adaptive digital systems having a loop in accordance with an objective function to adjust matrix parameter convergence to observable reference system dynamics. One way of complying with this condition is to use fuzzy logic inference mechanisms which interpret and select the best matrix parameter from a knowledge base. Such selection mechanisms with neural networks can provide a response from the best operational level for each change in state (Shannon, 1948). This paper considers the MIMO digital filter model usi
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Jonsson, Lena, Elzbieta Plaza, and Bengt Hultman. "Experiences of nitrogen and phosphorus removal in deep-bed filters in the Stockholm area." Water Science and Technology 36, no. 1 (1997): 183–90. http://dx.doi.org/10.2166/wst.1997.0042.

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Experimental studies of nutrient removal in a discontinuous downflow two-media filter on a pilot plant scale are described and compared with previously reported results from a continuous upflow filter (DynaSand) studied at full scale. Under controlled conditions both filters show low effluent values of total nitrogen and phosphorus. Removal mechanisms were more complex in the discontinuous downflow filter owing to the use of two media, deposition of sludge on the filter surface, and changes of the biological activity over time after backwashing. The discontinuous downflow filter was much influ
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Kang, Jieun, Heung-Kyu Ko, Ji Hoon Shin, et al. "Practice patterns of retrievable inferior vena cava filters and predictors of filter retrieval in patients with pulmonary embolism." Vascular Medicine 22, no. 6 (2017): 512–17. http://dx.doi.org/10.1177/1358863x17726596.

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Retrievable inferior vena cava (IVC) filters are increasingly used in patients with venous thromboembolism (VTE) who have contraindications to anticoagulant therapy. However, previous studies have shown that many retrievable filters are left permanently in patients. This study aimed to identify the common indications for IVC filter insertion, the filter retrieval rate, and the predictive factors for filter retrieval attempts. To this end, a retrospective cohort study was performed at a tertiary care center in South Korea between January 2010 and May 2016. Electronic medical charts were reviewe
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International Monetary Fund. "Estimating Potential Output with a Multivariate Filter." IMF Working Papers 10, no. 285 (2010): 1. http://dx.doi.org/10.5089/9781455210923.001.

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Blagrave, Patrick, Roberto Garcia-Saltos, Douglas Laxton, and Fan Zhang. "A Simple Multivariate Filter for Estimating Potential Output." IMF Working Papers 15, no. 79 (2015): 1. http://dx.doi.org/10.5089/9781475565133.001.

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ur Rehman, Naveed, and Danilo P. Mandic. "Filter Bank Property of Multivariate Empirical Mode Decomposition." IEEE Transactions on Signal Processing 59, no. 5 (2011): 2421–26. http://dx.doi.org/10.1109/tsp.2011.2106779.

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Thèses sur le sujet "Multivariate filter"

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SALMAN, RAMIZ. "Identification of common economic cycles using optimal multivariate filters." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2022. http://hdl.handle.net/10281/394321.

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This thesis includes two essays that are focused on developing multivariate filter approaches to be used for extracting common cyclical components where the common components can be used as an estimator of a business cycle. The first chapter aims to develop an optimal multivariate filter in order to extract common cyclical components of macroeconomic indicators. The filter allows macroeconomic series to be modeled as a phase shifted version of a coinciding business cycle (BC) while keeping other time series components such as the stochastic trend and idiosyncratic shocks intact (i.e. they are
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Pereira, Ana Regina Nunes. "Multivariate Filtering with Common Factors." Master's thesis, Instituto Superior de Economia e Gestão, 2009. http://hdl.handle.net/10400.5/1148.

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Mestrado em Econometria Aplicada e Previsão<br>This study discusses four commonly used optimal approximations to the infinite order moving average filter that ideally extracts from a time series fluctuations within a specified range of periodicities. Based on our findings, we use two of those approximations in the estimation of two macroeconomic signals: business cycle fluctuations and medium to long run component of output growth rate. This study dis-tinguishes itself from related literature by showing how to successfully incorporate in the multivariate band-pass approximations factors estima
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LUCCHESE, Gianfranco. "Multivariate hedonic models for heterogeneous product prices in dynamic supply chains." Doctoral thesis, Università degli studi di Bergamo, 2012. http://hdl.handle.net/10446/26713.

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Identifying parameters for state-space models in high dimensioned cases requires a complex methodology. We offer an example of application for hedonic prices and the hyper-parameter estimation for dynamic supply chains. An algorithm is created based on the Kalman filter-smoother and Expectation-Maximization procerures. Stopping rules for the algorithm are analyzed and compared. We detected the best stopping rule for our environment. In this way, the hedonic prices estimated can be used for any decision process. The thesis point to an application in forecast analysis for product prices. Accura
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Castellanos, Lucia. "Statistical Models and Algorithms for Studying Hand and Finger Kinematics and their Neural Mechanisms." Research Showcase @ CMU, 2013. http://repository.cmu.edu/dissertations/273.

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The primate hand, a biomechanical structure with over twenty kinematic degrees of freedom, has an elaborate anatomical architecture. Although the hand requires complex, coordinated neural control, it endows its owner with an astonishing range of dexterous finger movements. Despite a century of research, however, the neural mechanisms that enable finger and grasping movements in primates are largely unknown. In this thesis, we investigate statistical models of finger movement that can provide insights into the mechanics of the hand, and that can have applications in neural-motor prostheses, ena
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Marhaba, Bassel. "Restauration d'images Satellitaires par des techniques de filtrage statistique non linéaire." Thesis, Littoral, 2018. http://www.theses.fr/2018DUNK0502/document.

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Le traitement des images satellitaires est considéré comme l'un des domaines les plus intéressants dans les domaines de traitement d'images numériques. Les images satellitaires peuvent être dégradées pour plusieurs raisons, notamment les mouvements des satellites, les conditions météorologiques, la dispersion et d'autres facteurs. Plusieurs méthodes d'amélioration et de restauration des images satellitaires ont été étudiées et développées dans la littérature. Les travaux présentés dans cette thèse se concentrent sur la restauration des images satellitaires par des techniques de filtrage statis
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Lee, Anthony. "Towards smooth particle filters for likelihood estimation with multivariate latent variables." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/1547.

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In parametrized continuous state-space models, one can obtain estimates of the likelihood of the data for fixed parameters via the Sequential Monte Carlo methodology. Unfortunately, even if the likelihood is continuous in the parameters, the estimates produced by practical particle filters are not, even when common random numbers are used for each filter. This is because the same resampling step which drastically reduces the variance of the estimates also introduces discontinuities in the particles that are selected across filters when the parameters change. When the state variables are univa
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Al, Chaer Toufic. "Robust control of multivariable systems : application to a three-phase shunt active filter in low voltage electrical networks." Poitiers, 2008. http://www.theses.fr/2008POIT2352.

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The work done in this thesis aims to combine the knowledge of two research areas: the automatic control area and the power electronics area, in order to elaborate a methodology for controlling a three-phase shunt active filter system. Indeed, this subject has been widely handled by the specialists in the field of power electronics in order to eliminate voltage and current harmonics in electrical distribution networks. Most of existing control strategies of active filters have been formulated as a current reference tracking control design problem. The alternative approach that we propose is to
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Cunha, Camilla Lima. "Estudo da previsão de propriedades do biodiesel utilizando espectros de infravermelho e calibração multivariada." Universidade do Estado do Rio de Janeiro, 2014. http://www.bdtd.uerj.br/tde_busca/arquivo.php?codArquivo=7293.

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O biodiesel tem sido amplamente utilizado como uma fonte de energia renovável, que contribui para a diminuição de demanda por diesel mineral. Portanto, existem várias propriedades que devem ser monitoradas, a fim de produzir e distribuir biodiesel com a qualidade exigida. Neste trabalho, as propriedades físicas do biodiesel, tais como massa específica, índice de refração e ponto de entupimento de filtro a frio foram medidas e associadas a espectrometria no infravermelho próximo (NIR) e espectrometria no infravermelho médio (Mid-IR) utilizando ferramentas quimiométricas. Os métodos de regressão
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Plappally, Anand Krishnan. "Theoretical and Empirical Modeling of Flow, Strength, Leaching and Micro-Structural Characteristics of V Shaped Porous Ceramic Water Filters." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1276860054.

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Frey, Roman. "Monte Carlo methods with application to the pricing of interest rate derivatives /." St. Gallen, 2008. http://www.biblio.unisg.ch/org/biblio/edoc.nsf/wwwDisplayIdentifier/03393436001/$FILE/03393436001.pdf.

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Livres sur le sujet "Multivariate filter"

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Laxton, Douglas. A simple multivariate filter for the measurement of potential output. Bank of Canada, 1992.

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Laxton, Douglas. A simple multivariate filter for the measurement of potential output. Bank of Canada, 1992.

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Benes, Jaromir. A multivariate filter for measuring potential output and the NAIRU: Application to the Czech Republic. International Monetary Fund, Asia and Pacific Dept., 2004.

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Öhrn, Kenth. Design of multivariable cautious discrete-time Wiener filters: A probabilistic approach. Uppsala University, 1996.

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Khattree, Ravindra. Applied multivariate statistics with SAS software. 2nd ed. SAS Institute, 1999.

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L, Hershberger Scott, ed. Multivariate statistical methods: A first course. Lawrence Erlbaum Associates, 1997.

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N, Naik Dayanand, ed. Applied multivariate statistics with SAS software. 2nd ed. SAS Institute, 1999.

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N, Naik Dayanand, ed. Applied multivariate statistics with SAS software. SAS Institute, 1995.

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Jean, Stafford. L' analyse multivariée avec SPSS. Presses de l'Université du Québec, 2006.

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Abu-Bader, Soleman H. Advanced & multivariate statistical methods for social science research: With complete SPSS guide. Lyceum Books, 2010.

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Chapitres de livres sur le sujet "Multivariate filter"

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Stronegger, Willi-Julius. "Kalman Filter zur On-Line-Diskriminanz-Analyse von Verlaufskurven." In Multivariate Modelle. Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-95669-0_6.

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Jadid Abdulkadir, Said, and Suet-Peng Yong. "Unscented Kalman Filter for Noisy Multivariate Financial Time-Series Data." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-44949-9_9.

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Blough, David K. "Intervention Analysis in Multivariate Time Series via the Kalman Filter." In Estimation and Analysis of Insect Populations. Springer New York, 1989. http://dx.doi.org/10.1007/978-1-4612-3664-1_28.

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Xu, Yonghong, Wenxue Hong, Na Chen, Xin Li, WenYuan Liu, and Tao Zhang. "Parallel Filter: A Visual Classifier Based on Parallel Coordinates and Multivariate Data Analysis." In Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74205-0_121.

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Boonkla, Surasak, Masashi Unoki, and Stanislav S. Makhanov. "Robust Speech Analysis Based on Source-Filter Model Using Multivariate Empirical Mode Decomposition in Noisy Environments." In Speech and Computer. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-43958-7_70.

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Zeng, An, Dan Pan, Yang Haidong, and Xie Guangqiang. "Applications of Multivariate Time Series Analysis, Kalman Filter and Neural Networks in Estimating Capital Asset Pricing Model." In Modern Advances in Applied Intelligence. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07467-2_53.

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Frühwirth-Schnatter, Sylvia. "Monitoring von ökologischen und biometrischen Prozessen mit statistischen Filtern." In Multivariate Modelle. Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/978-3-642-95669-0_5.

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Triantafyllopoulos, K. "Multivariate Stochastic Volatility Estimation Using Particle Filters." In Springer Proceedings in Mathematics & Statistics. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0569-0_30.

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Li, Wenbin, Ning Zhong, and Chunnian Liu. "Combining Multiple Email Filters Based on Multivariate Statistical Analysis." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11875604_81.

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Wang, Jian. "Dynamic Correlation Integration of Multivariable System with Input and Output Filter." In A Self Adaptive Real Time Optimization for Stochastic Dynamic System. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-0632-0_9.

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Actes de conférences sur le sujet "Multivariate filter"

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Qais, Emad, and M. N. Veena. "Arabic Short Text Analytics using Multivariate Filter Methods and ProdLDA Model." In 2024 Second International Conference on Networks, Multimedia and Information Technology (NMITCON). IEEE, 2024. http://dx.doi.org/10.1109/nmitcon62075.2024.10699211.

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Yu, Zesheng, Hongxu Zhang, Ming Gao, Yuxiao Hu, and Yutong Guan. "A Gaussian Filter for High-Dimensional State-Space Models with State Partition and Multivariate Laplace Distribution." In 2025 7th International Conference on Information Science, Electrical and Automation Engineering (ISEAE). IEEE, 2025. https://doi.org/10.1109/iseae64934.2025.11042245.

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Hari, Gautam, Nrushad Joshi, Zhe Wang, et al. "FunM2C: A Filter for Uncertainty Visualization of Multivariate Data on Multi-Core Devices." In 2024 IEEE Workshop on Uncertainty Visualization: Applications, Techniques, Software, and Decision Frameworks. IEEE, 2024. http://dx.doi.org/10.1109/uncertaintyvisualization63963.2024.00010.

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Zhang, Ming, Ruitao Zhang, and Jiaqun Xu. "Multivariable Reconstruction for Permanent Magnet Synchronous Motor with Input Filter Based on Extended State Variable." In 2024 4th International Conference on Electronic Information Engineering and Computer Communication (EIECC). IEEE, 2024. https://doi.org/10.1109/eiecc64539.2024.10929246.

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Nam Anh, Dao. "Multivariate Filter for Saliency." In 2018 1st International Conference on Multimedia Analysis and Pattern Recognition (MAPR). IEEE, 2018. http://dx.doi.org/10.1109/mapr.2018.8337522.

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Abdul-Rahman, Shuzlina, Zeti-Azura Mohamed-Hussein, and Azuraliza Abu Bakar. "Multivariate filter and PSO in protein function classification." In 2010 International Conference of Soft Computing and Pattern Recognition (SoCPaR). IEEE, 2010. http://dx.doi.org/10.1109/socpar.2010.5686158.

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Soyemi, Olusola O., Paul J. Gemperline, Lixia Zhang, DeLyle Eastwood, Hong Li, and Michael L. Myrick. "Novel filter design algorithm for multivariate optical computing." In Environmental and Industrial Sensing, edited by Tuan Vo-Dinh and Stephanus Buettgenbach. SPIE, 2001. http://dx.doi.org/10.1117/12.417462.

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Bollenbeck, Felix, Andreas Backhaus, and Udo Seiffert. "A multivariate wavelet-PCA denoising-filter for hyperspectral images." In 2011 3rd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS). IEEE, 2011. http://dx.doi.org/10.1109/whispers.2011.6080901.

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Zucchelli, Enrico M., and Brandon A. Jones. "A Gaussian Integral Filter with Multivariate Laplace Process Noise." In 2023 26th International Conference on Information Fusion (FUSION). IEEE, 2023. http://dx.doi.org/10.23919/fusion52260.2023.10224147.

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Daojing Wang, Chao Zhang, and Xuemin Zhao. "Multivariate Laplace Filter: A heavy-tailed model for target tracking." In 2008 19th International Conference on Pattern Recognition (ICPR). IEEE, 2008. http://dx.doi.org/10.1109/icpr.2008.4761002.

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Rapports d'organisations sur le sujet "Multivariate filter"

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De Castro-Valderrama, Marcela, Santiago Forero-Alvarado, Nicolás Moreno-Arias, and Sara Naranjo-Saldarriaga. Unraveling the Exogenous Forces Behind Analysts' Macroeconomic Forecasts. Banco de la República, 2021. http://dx.doi.org/10.32468/be.1184.

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Modern macroeconomics focuses on the identification of the primitive exogenous forces generating business cycles. This is at odds with macroeconomic forecasts collected through surveys, which are about endogenous variables. To address this divorce, our paper uses a general equilibrium model as a multivariate filter to infer the shocks behind market analysts' forecasts and thus, unravel their implicit macroeconomic stories. By interpreting all analysts' forecasts through the same lenses, it is possible to understand the differences between projected endogenous variables as differences in the ty
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Clark, Todd E., Gergely Ganics, and Elmar Mertens. Constructing fan charts from the ragged edge of SPF forecasts. Federal Reserve Bank of Cleveland, 2022. http://dx.doi.org/10.26509/frbc-wp-202236.

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We develop a model that permits the estimation of a term structure of both expectations and forecast uncertainty for application to professional forecasts such as the Survey of Professional Forecasters (SPF). Our approach exactly replicates a given data set of predictions from the SPF (or a similar forecast source) without measurement error. Our model captures fixed horizon and fixed-event forecasts, and can accommodate changes in the maximal forecast horizon available from the SPF. The model casts a decomposition of multi-period forecast errors into a sequence of forecast updates that may be
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