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265
Inference for SDE models via approximate Bayesian computation
 Journal of Computational and Graphical Statistics
"... Models defined by stochastic differential equations (SDEs) allow for the representation of random variability in dynamical systems. The relevance of this class of models is growing in many applied research areas and is already a standard tool to model e.g. financial, neuronal and population growth d ..."
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Cited by 5 (3 self)
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dynamics. However inference for multidimensional SDE models is still very challenging, both computationally and theoretically. Approximate Bayesian computation (ABC) allow to perform Bayesian inference for models which are sufficiently complex that the likelihood function is either analytically
Partially Observable SDE Models for Image Sequence Recognition Tasks
 Advances in Neural Information Processing Systems, number 13
"... This paper explores a framework for recognition of image sequences using partially observable stochastic differential equation (SDE) models. MonteCarlo importance sampling techniques are used for efficient estimation of sequence likelihoods and sequence likelihood gradients. Once the network dynami ..."
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Cited by 5 (3 self)
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This paper explores a framework for recognition of image sequences using partially observable stochastic differential equation (SDE) models. MonteCarlo importance sampling techniques are used for efficient estimation of sequence likelihoods and sequence likelihood gradients. Once the network
Fitting SDE models to nonlinear Kac–Zwanzig heat bath models
, 2004
"... We study a class of “particle in a heat bath ” models, which are a generalization of the wellknown Kac–Zwanzig class of models, but where the coupling between the distinguished particle and the n heat bath particles is through nonlinear springs. The heat bath particles have random initial data draw ..."
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We study a class of “particle in a heat bath ” models, which are a generalization of the wellknown Kac–Zwanzig class of models, but where the coupling between the distinguished particle and the n heat bath particles is through nonlinear springs. The heat bath particles have random initial data
CHANGE POINT TEST FOR DISPERSION PARAMETER BASED ON DISCRETELY OBSERVED SAMPLE FROM SDE MODELS
"... Abstract. In this paper, we consider the cusum of squares test for the dispersion parameter in stochastic differential equation models. It is shown that the test has a limiting distribution of the sup of a Brownian bridge, unaffected by the drift parameter estimation. A simulation result is provide ..."
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Abstract. In this paper, we consider the cusum of squares test for the dispersion parameter in stochastic differential equation models. It is shown that the test has a limiting distribution of the sup of a Brownian bridge, unaffected by the drift parameter estimation. A simulation result
Approximate Bayesian computation in state space models. 2014. arXiv:1409.8363. U. Picchini. Inference for SDE models via approximate Bayesian computation
"... A new approach to inference in state space models is proposed, based on approximate Bayesian computation (ABC). ABC avoids evaluation of the likelihood function by matching observed summary statistics with statistics computed from data simulated from the true process; exact inference being feasible ..."
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Cited by 2 (0 self)
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A new approach to inference in state space models is proposed, based on approximate Bayesian computation (ABC). ABC avoids evaluation of the likelihood function by matching observed summary statistics with statistics computed from data simulated from the true process; exact inference being
Name SDE Restrictions
"... The General Method of Moments (GMM) is an estimation technique which can be used for variety of financial models. We use the CKLS class of interest rate models to demonstrate how GMM works. We discuss the practical implementation in MATLAB. We pay attention to exactlyidentified versus overidentif ..."
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ShortTerm Interest Rate Stochastic Differential Equation The dynamics of a shortterm interest rate can be nested within the following stochastic differential equation (SDE): drt = (α+ βr)dt+ σrγdZt, (1) where α, β, σ, γ are model parameters, rt is the shortterm interest rate and Zt is the standard
Consider the onedimensional Itô SDE
, 2008
"... Researchers are interested in using differential equations to modelize the dynamics of physical phenomena. However analytic solutions to general systems of differental equations are often unavailable Computer based numerical strategies are necessary to overcome such difficulty ..."
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Researchers are interested in using differential equations to modelize the dynamics of physical phenomena. However analytic solutions to general systems of differental equations are often unavailable Computer based numerical strategies are necessary to overcome such difficulty
Modeling UserProvided Whitespace and Comments in an Incremental SDE
, 1988
"... INTRODUCTION Whitespace plays several roles in programming languages: it separates other tokens, provides the programmer with a degree of control over the visual presentation of the source code, and in some languages even serves as a syntactic construct. Batch compilers and environments handle whit ..."
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INTRODUCTION Whitespace plays several roles in programming languages: it separates other tokens, provides the programmer with a degree of control over the visual presentation of the source code, and in some languages even serves as a syntactic construct. Batch compilers and environments handle whitespace in a simple manner, discarding it as the lexical analyzer scans each region of the text. y Incremental environments, This research has been sponsored in part by the Advanced Research Projects Agency (ARPA) under Grant MDA97292J1028, and in part by NSF institutional infrastructure grant CDA8722788. The content of this paper does not necessarily reflect the position or policy of the U. S. Government. Authors' addresses: Tim A. Wagner, Reasoning, Inc., 700 E. El Camino, Suite #300, Mountain View, CA 94040 and Susan L. Graham, 771 Soda Hall; Department of Electrical Engineering and Computer Science, Computer Science Division, University o
Results 1  10
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265