搜索结果: 1-10 共查到“统计学 state space”相关记录10条 . 查询时间(0.156 秒)
MCMC for non-linear state space models using ensembles of latent sequences
MCMC non-linear state space models ensembles latent sequences
2013/6/13
Non-linear state space models are a widely-used class of models for biological, economic, and physical processes. Fitting these models to observed data is a difficult inference problem that has no str...
Propagation of initial errors on the parameters for linear and Gaussian state space models
Kalman filter Extended Kalman filter State space mod-els Autoregressive process
2013/4/27
For linear and Gaussian state space models parametrized by $\theta_0 \in \Theta \subset \R^{r}, r \geq 1$ corresponding to the vector of parameters of the model, the Kalman filter gives exactly the so...
On some problems in the article “Efficient Likelihood Estimation in State Space Models” by Cheng-Der Fuh
problems Efficient Likelihood Estimation State Space Models
2010/3/11
Upon reading the paper Efficient Likelihood Estimation
in State Space Models by Cheng-Der Fuh I found a number of problems in the
formulations and a number of mathematical errors. Together, these fi...
On zero - sum stochastic games with general state space. I
zero - sum stochastic games general state space
2009/9/24
On zero - sum stochastic games with general state space. I。
On zero-sum stochastic games with general state space. II
zero-sum stochastic games general state space
2009/9/24
On zero-sum stochastic games with general state space. II。
MARKOV PROCESSES CONDITIONED TO NEVER EXIT A SUBSPACE QF THE STATE SPACE
Markov process extended generator exponential change of measure
2009/9/21
In this paper we study Markov processes never exiting
(NE) a subspace A of the state space E or, in other words, Markov
processes conditioned to stay in the subspace A. We show bow the
knowledge of...
This paper surveys various results about Markov chains on general (non-countable) state spaces. It begins with an introduction to Markov chain Monte Carlo (MCMC) algorithms, which provide the motivati...
State-space based mass event-history model I：many decision-making agents with one target
Extremists Heterogeneity Interval censoring Logistic regression Maximum likelihood estimation Nematode
2010/3/17
A dynamic decision-making system that includes a mass of indistinguishable
agents could manifest impressive heterogeneity. This
kind of nonhomogeneity is postulated to result from macroscopic behavi...
State Space Realization Theorems For Data Mining
realizations formal series learning sets data mining Myhill–Nerode Theorem input-output maps algebraic approaches todata mining
2010/3/17
In this paper, we consider formal series associated with events, profiles
derived from events, and statistical models that make predictions
about events. We prove theorems about realizations for the...
A State-Space Mixed Membership Block model for Dynamic Network Tomography
Dynamic network modeling Mixed membership stochasticblock models
2010/3/17
In a dynamic social or biological environment, the interactions
between the underlying actors can undergo large and systematic
changes. The latent roles or membership of the actors as determined
by...