dynamic state-space models
Fast sequential parameter inference for dynamic state space models
... general state-space models are examples of such inference ...the dynamic spectrum problem discussed above is processing received data sequentially rather than in a batch and this idea is best ...
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Dynamic State Space Models
... The impetus for the popularity of Factor models in finance can probably be attributed to the sem- inal paper on Arbitrage Pricing Theory by Ross (1976). The CAPM model of Sharpe (1970) generated a linear security ...
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Least Squares Matrix Algorithm for State Space Modelling of Dynamic Systems
... In this work we describe the least squares matrix (LSM) algorithm for the estimation of the dynamic state-space models. In conventional recursive least squares (RLS) algorithms uptake is based ...
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Small Signal Stability Analysis of Synchronous Generators Connected to Infinite Bus
... Dynamic stability analysis has been made in this paper for 210 MW turbo generator set using both flux-linkage and current state space models for different conditions of loading. While the ...
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Searching Multiregression Dynamic Models of Resting-State fMRI Networks Using Integer Programming
... model space can be scored ...MDM models dynamic links and so allows us to discriminate between models that would be Markov equivalent in their static ...model space we need to search is ...
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Reparametrized Dynamic Space-Time Models and Spatial Model Selection
... of space-time data sets can be very large, and moreover, space-time processes are often complicated in that the dependence structure across space and time is non-trivial, often non-separable and ...
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The state space models toolbox for MATLAB
... a state space matrix, with elements marked as variable (dependent on model parameters) and/or dynamic (dependent on ...from state space matrices is ...smoothed state, and the ...
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Moving Towards Predictive Toxicology - A Systems Biology Approach
... molecular state of cell-lines and tissues across many di ff erent ...steady state and prior knowl- edge to be ...data. State space models and ODE based approaches are used to develop ...
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Dynamic probabilities of restrictions in state space models: an application to the Phillips curve
... Φορ ινστανχε, ιφ Χ ισ τηε στανδαρδ …ρστ−δι¤ερενχε mατριξ ανδ χ = 0 τηεν τηε ρεστριχτιονσ οφ ιντερεστ αρε 1 = 2 = :: = Τ ανδ τηε παραmετερσ αρε νοτ τιmε ϖαρψινγ αλτηουγη, ασ νοτεδ ιν τηε [r] ...
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Efficient State-Space Inference of Periodic Latent Force Models
... thermal models of home heating ...thermal models suggest; sunlight through windows contributes to extra heat while open windows cause heat ...the dynamic system in this application is linear and ...
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Model-Based Diagnosis of Hybrid Systems Using Satisfiability Modulo Theory
... modelling dynamic system behaviour is done through well-known state space models using dif- ferential ...the state space models we calculate Boolean residuals through an ...
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Modeling Monthly Rainfall Time Series Using Ets State Space And Sarima Models
... ETS state space models are within the limits upon which the models are based, therefore the residuals are white noise suggesting that the models are adequate following (Ramasubramanian, ...
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The frequency response of dynamic friction: Enhanced rate-and-state models
... some models for dynamic friction taken from the ...the models tested were able to give even qualitative agreement with the measurements, and this left a ...and state ” models, developed ...
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Initial Values in Estimation Procedures for State Space Models (SSMs)
... the Kalman filter under the normality assumption for SSM are provided in Durbin and Koopman ([13], Chapter 5 and references therein). Several other suggestions on initialisation for the state variable in SSM under ...
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Forecasting VARMA processes using VAR models and subspace based state space models
... series, state-space-based system-identification methods present some additional advantages over VARMA modelling, especially for the specification step: there is only one hyperparameter to estimate, namely ...
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Bootstrap Approximation to Prediction MSE for State Space Models with Estimated Parameters
... the state vector predictors use estimated hyper-parameter ...the state vectors and the measured ...of state-space models has been considered before by Stoffer and Wall (1991, 2002), but ...
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Small area estimation with state space models subject to benchmark constraints
... individual State models into a joint model with built in benchmark constrains intensifies the ...the state vector in the separate State models is 30 (see next section), implying that by ...
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Particle Filters and Data Assimilation
... Figure 3: Left-hand column: results from the simple smoother of Kitagawa (1996) for the stochastic volatility model; right-hand column: results from the forward-backward smoother. Top plots show the paths stored after ...
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Randomness, Determinism and Undecidability in the Economic cycle Theory
... The Keynesian and neo-Keynesian theories don´t start from a representative agent or maximizing agents inter-temporally, but from macroeconomic variables in a holistic approach. Except, the school of thoughts that uses ...
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Aluminium and base cation chemistry in dynamic acidification models – need for a reappraisal?
... used models as regards to base cations and aluminium, and then to investigate the difference in model performance between the two types of model mentioned above, ...ion-exchange models and organic com- ...
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