Results 261 to 270 of about 513,377 (289)

Forecasting volatility with interacting multiple models

Finance Research Letters, 2017
Abstract We examine the performance of Kalman filter techniques in forecasting volatility. We find that the simple implementation of an online Kalman filtering procedure that combines commonly used forecasting models with market-based estimates improves the accuracy of volatility forecasts.
Jiri Svec, Xerxis Katrak
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Interacting multiple model particle filter

IEE Proceedings - Radar, Sonar and Navigation, 2003
A new method for multiple model particle filtering for Markovian switching systems is presented. This new method is a combination of the interacting multiple model (IMM) filter and a (regularised) particle filter. The mixing and interaction is similar to that in a conventional IMM filter. However, in every mode a regularised particle filter is running.
Y. Boers, J.N. Driessen
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Interacting Multiple Model LK Tracking

Applied Mechanics and Materials, 2014
The nonlinear motion state of object seriously affects the object tracking characteristics in complex motion scene. In this paper, we propose an interacting multiple model LK (IMM-LK) tracking algorithm to enhance the performance of tracking nonlinear moving object.
Hong Wang, Jia Deng
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Models of Multiple Interactions from Collinear Patterns

2018
Each collinear pattern should be made up of a large number of feature vectors which are located on a plane in a multidimensional feature space. Data subset located on a plane can represent linear interactions between multiple variables (features, genes).
Leon Bobrowski, Pawel Zabielski
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Testing Subhypotheses in the Multiplicative Interaction Model

Technometrics, 1981
The problem of analyzing a two-way cross-classified treatment structure with only one observation per treatment combination is considered. A test procedure is given that will enable the data analyst to determine subareas of the data in which the data are additive. The procedure is developed by assuming that a multiplicative interaction model adequately
Mervyn G. Marasinghe, Dallas E. Johnson
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Asymptotic variances for the multiplicative interaction model

Journal of Applied Statistics, 1991
When modelling two-way analysis of variance interactions by a multiplicative term-[Formula] asymptotic variances and covariances are derived for the parameters p, yi and Sj using maximum likelihood theory. The asymptotic framework is defined by a2/K where K is the number of observations per combination of the two factors and a2 the common variance of ...
Chadoeuf, Joel, J., Denis, J.B.
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Deep Interacting Multiple Model Filtering

2022 American Control Conference (ACC), 2022
Ghananeel Rotithor, Ashwin P. Dani
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Multiple interactions: An empirically suggested model

Theoretical Population Biology, 1982
Abstract A modified version of Schoener's non-linear competition model is presented. The model describes the competitive dynamics of two species competing for a common resource. A second resource made available by species 1 for the exclusive use of species 2 is also present.
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Multiple Models — Fixed, Switching, Interacting

2004
In dynamic models the dynamic and the observation equations are based on a known system model. The multiple model approach introduces uncertainties about the system model by a set of possible system models. In the multiple model approach for fixed models the true system does not change during the whole observation process, wheareas in the approach for ...
Brigitte Gundlich, Peter Teunissen
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The continuous time roots of the Interacting Multiple Model filter

2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 2012
The Interacting Multiple Model (IMM) filter has become a benchmarking reference in discrete time filtering of Markov jump linear systems, and one of the most popular maneuvering target tracking approaches. Although the IMM filter is typically known in discrete time setting, it has originally been developed in a pure continuous time setting in a 1982 ...
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