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The parameters of temporal models, such as dynamic Bayesian networks, may be modelled in a Bayesian context as static or atemporal variables that influence transition probabilities at every time step....
Parameter estimation for fractional birth and fractional death processes
birth process Yule process Yule{Furry process death process Mittag{Leer
2013/4/28
The fractional birth and the fractional death processes are more desirable in practice than their classical counterparts as they naturally provide greater flexibility in modeling growing and decreasin...
A parameter estimation method based on random slow manifolds
Parameter estimation Slow-fast system Random slow manifold Quantifying uncer-tainty Numerical optimization
2013/5/2
A parameter estimation method is devised for a slow-fast stochastic dynamical system, where often only the slow component is observable. By using the observations only on the slow component, the syste...
Parameter estimation in high dimensional Gaussian distributions
high dimensional Gaussian Parameter estimation massive memory
2011/6/20
In order to compute the log-likelihood for high dimensional spatial Gaussian models, it is
necessary to compute the determinant of the large, sparse, symmetric positive definite precision
matrix, Q....
Adaptive estimator of the memory parameter and goodness-of-fit test using a multidimensional increment ratio statistic
Long-memory Gaussian processes goodness-of-fit test estimation of the memory parameter
2010/10/14
The Increment Ratio (IR) statistic was first defined and studied in Surgailis {\it et al.} (2008) for estimating the long-memory parameter either of a stationary or an increment stationary Gaussian p...