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Estimation of Continuous-time Markov Processes Sampled at Random Time Intervals
Method of moments parameter estimation Markov process
2015/7/6
We introduce a family of generalized-method-of-moments estimators of the parameters of a continuous-time Markov process observed at random time intervals. The results include strong consistency, asymp...
This paper is a note on the use of Bayesian nonparametric mixture models for continuous time series. We identify a key requirement for such models, and then establish that there is a single type of mo...
An EM Algorithm for Continuous-time Bivariate Markov Chains
Parameter estimation EM algorithm Continuous-time bivariate Markov chain
2011/7/19
We study properties and parameter estimation of finite-state homogeneous continuous-time bivariate Markov chains.
A martingale approach to continuous time marginal structural models
martingale approach continuous time marginal structural models
2010/3/17
Marginal structural models were introduced in order to provide
estimates of causal effects from interventions based on observational studies
in epidemiological research. We present a variant of the ...
Parameter Estimation in Continuous Time Markov Switching Models: A Semi-Continuous Markov Chain Monte Carlo Approach
Bayesian inference data augmentation hidden Markov model
2009/9/24
In this paper,we combine useful aspects of both approaches.On the one hand,we are inspired by the discretization, where filtering for the state process is possible,on the other hand,we
catch attracti...
Application of Girsanov Theorem to Particle Filtering of Discretely Observed Continuous-Time Non-Linear Systems
Girsanov theorem particle ltering continuous-discrete ltering
2009/9/22
This article considers the application of particle ltering to continuous-
discrete optimal ltering problems, where the system model is a stochastic dier-
ential equation, and noisy measurements of t...
Non-Parametric Volatility Estimation in Continuous Time
Non-Parametric Volatility Estimation Continuous Time
2009/9/17
Non-Parametric Volatility Estimation in Continuous Time。
Maximum Likelihood Estimator for Hidden Markov Models in continuous time
Maximum Likelihood Estimator continuous time Hidden Markov Models partial observations filtering
2010/4/30
The paper studies large sample asymptotic properties of the
Maximum Likelihood Estimator (MLE) for the parameter of a continuous
time Markov chain, observed in white noise. Using the method of
weak...
On the Novikov-Shiryaev Optimal Stopping Problems in Continuous Time
Levy processes optimal stopping problem Appell polynomials pasting principles
2009/4/24
Novikov and Shiryaev (2004) give explicit solutions to a class of optimal stopping problems for random walks based on other similar examples given in Darling et al. (1972). We give the analogue of the...
On the Goodness-of-Fit Tests for Some Continuous Time Processes
Hypotheses testing diffusion process Poisson process selfexcitingprocess goodness-of-fit tests
2010/3/19
We present a review of several results concerning the construction
of the Cram´er-von Mises and Kolmogorov-Smirnov type goodnessof-
fit tests for continuous time processes. As the models we ta...
Continuous-time trading and the emergence of volatility
Continuous-time trading emergence of volatility
2009/3/20
This note continues investigation of randomness-type properties emerging in idealized financial markets with continuous price processes. It is shown, without making any probabilistic assumptions, that...
Regression Estimation and Prediction in Continuous Time
Continuous time nonparametric prediction nonparametric regression
2009/3/5
This paper studies the nonparametric regression estimation and the prediction problem for continuous-time observations. The almost sure convergence of a kernel regression estimator and the associated ...
Local superefficiency of data-driven projection density estimators in continuous time
Density estimation data-driven superefficiency continuous time processes
2009/2/23
We construct a data-driven projection density estimator for continuous time processes. This estimator reaches superoptimal rates over a class F0 of densities that is dense in the family of all possibl...
A matrix function useful in the estimation of linear continuous-time models
matrix derivatives vectorization matrix exponential
2009/2/23
In a recent publication Chen & Zadrozny (2001) derive some equations for efficiently computing eA and ∇eA, its derivative. They employ an expression due to Bellman (1960), Snider (1964) and Wilc...
On continuous-time autoregressive fractionally integrated moving average processes
antipersistence autocovariance fractional Brownian motion long memory spectraldensity
2010/3/18
In this paper, we consider a continuous-time autoregressive fractionally integrated moving average(CARFIMA) model, which is defined as the stationary solution of a stochastic differential
equation dr...