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On spatial processes and asymptotic inference under near-epoch dependence
Random fields Near-epoch dependent processes Central limit theorem Law of large numbers GMM estimator
2015/9/24
The development of a general inferential theory for nonlinear models with cross-sectionally or spatially dependent data has been hampered by a lack of appropriate limit theorems. To facilitate a gener...
Inference of Extreme Synchrony with an Entropy Measure on a Bipartite Network
Extreme Synchrony Entropy Measure Bipartite Network
2012/9/14
This article proposes a method to quantify the structure of abipartite graph with a network entropy from a statistical–physical point of view. The network entropy of a bipartite graph with random link...
Bayesian Inference of Stochastic Volatility Model by Hybrid Monte Carlo
Hybrid Monte Carlo Algorithm Stochastic Volatility Model
2010/10/18
The hybrid Monte Carlo (HMC) algorithm is applied for the Bayesian inference of the stochastic volatility (SV) model. We use the HMC algorithm for the Markov chain Monte Carlo updates of volatility va...
Inference on multivariate ARCH processes with large sizes
Inference multivariate ARCH processes large sizes
2010/10/29
The covariance matrix is formulated in the framework of a linear multivariate ARCH
process with long memory, where the natural cross product structure of the covariance is
generalized by adding two ...
Bayesian Inference on QGARCH Model Using the Adaptive Construction Scheme
Bayesian Adaptive Construction Scheme
2010/11/1
We study the performance of the adaptive construction scheme for a Bayesian inference on the Quadratic GARCH model which introduces the asymmetry in time series dynamics.In the adaptive construction s...
Bayesian inference with an adaptive proposal density for GARCH models
Bayesian inference adaptive proposal GARCH models
2010/11/2
We perform the Bayesian inference of a GARCH model by the Metropolis-Hastings algorithm with an adaptive proposal density. The adaptive proposal density is assumed to be the Student’s t-distribution a...
Likelihood Inference for Diffusions: A Survey.
INFERENCE IN LINEAR TIME SERIES MODELS WITH SOME UNIT ROOTS
Cointegration error correction models vector autoregressio
2014/3/18
This paper considers estimation and hypothesis testing in linear time series models when some or all of the variables have unit roots. Our motivating example is a vector auto...