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Quadratic Approximate Dynamic Programming for Input-Affine Systems
approximate dynamic programming stochastic control convex optimization
2015/7/9
We consider the use of quadratic approximate value functions for stochastic control problems with input-affine dynamics and convex stage cost and constraints. Evaluating the approximate dynamic progra...
Equation-free dynamic renormalization in a glassy compaction model
In combination with dynamic renormalization evolutionary dynamics accelerated simulator glass dynamic phenomenon
2014/12/25
Combining dynamic renormalization with equation-free computational tools, we study the apparently asymptotically self-similar evolution of void distribution dynamics in the diffusion-deposition proble...
Structural and Functional Discovery in Dynamic Networks with Non-negative Matrix Factorization
Structural Functional Discovery Dynamic Networks Non-negative Matrix Factorization
2013/6/17
Time series of graphs are increasingly prevalent in modern data and pose unique challenges to visual exploration and pattern extraction. This paper describes the development and application of matrix ...
Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture
Dynamic Clustering Asymptotics Dependent Dirichlet Process Mixture
2013/6/17
This paper presents a novel algorithm, based upon the dependent Dirichlet process mixture model (DDPMM), for clustering batch-sequential data containing an unknown number of evolving clusters. The alg...
An ANOVA Test for Parameter Estimability using Data Cloning with Application to Statistical Inference for Dynamic Systems
Maximum Likelihood Estimation Over -Parametrized Models Markov Chain Monte Carlo Parameter Identifiability Differential Equation Models
2013/6/14
Models for complex systems are often built with more parameters than can be uniquely identified by available data. Because of the variety of causes, identifying a lack of parameter identifiability typ...
Modeling Temporal Activity Patterns in Dynamic Social Networks
Activity Profile Modeling Twitter Data-Fitting Explanation Prediction Hidden Markov Model Coupled Hidden Markov Model Social Network In uence User Clustering
2013/6/14
The focus of this work is on developing probabilistic models for user activity in social networks by incorporating the social network influence as perceived by the user. For this, we propose a coupled...
A Robust Bayesian Dynamic Linear Model to Detect Abrupt Changes in an Economic Time Series: The Case of Puerto Rico
Dynamic Models Consumer Price Index Bayesian Robustness
2013/4/28
Economic indicators time series are usually complex with high frequency data. The traditional time series methodology requires at least a preliminary transformation of the data to get stationarity. On...
Modeling US house prices by spatial dynamic structural equation models
house prices Bayesian inference dynamic factor models spatio-temporal models cointegration lattice data
2013/4/27
This article proposes a spatial dynamic structural equation model for the analysis of housing prices at the State level in the USA. The study contributes to the existing literature by extending the us...
Combining Dynamic Predictions from Joint Models for Longitudinal and Time-to-Event Data using Bayesian Model Averaging
Prognostic Modeling Risk Prediction
2013/4/27
The joint modeling of longitudinal and time-to-event data is an active area of statistics research that has received a lot of attention in the recent years. More recently, a new and attractive applica...
Approximate Propagation of both Epistemic and Aleatory Uncertainty through Dynamic Systems
Uncertainty Propagation Epistemic Uncertainty Aleatory Uncertainty Dempster-Shafer
2011/7/19
When ignorance due to the lack of knowledge, modeled as epistemic uncertainty using Dempster-Shafer structures on closed intervals, is present in the model parameters, a new uncertainty propagation me...
Approximate group context tree: applications to dynamic programming and dynamic choice models
categorical time series group context tree
2011/7/19
The paper considers a variable length Markov chain model associated with a group of stationary processes that share the same context tree but potentially different conditional probabilities.
A Dynamic Spatio-temporal Precipitation Model
Rainfall modeling Space-time model Bayesian hierarchical model Markov chain Monte Carlo (MCMC) method Censoring Gaussian random fi eld
2011/3/24
A spatio-temporal model for precipitation is presented. Modeling the continuous and the discrete part of rainfall together, it is assumed that precipitation has a censored and power-transformed normal...
A Dynamic Spatio-temporal Precipitation Model
Rainfall modeling Space-time model Bayesian hierarchical model Markov chain Monte Carlo (MCMC) method Censoring Gaussian random fi eld
2011/3/24
A spatio-temporal model for precipitation is presented. Modeling the continuous and the discrete part of rainfall together, it is assumed that precipitation has a censored and power-transformed normal...
A Dynamic Spatio-temporal Precipitation Model
Rainfall modeling Space-time model Bayesian hierarchical model Markov chain Monte Carlo (MCMC) method Censoring Gaussian random fi eld
2011/3/23
A spatio-temporal model for precipitation is presented. Modeling the continuous and the discrete part of rainfall together, it is assumed that precipitation has a censored and power-transformed normal...
A Dynamic Analysis of Segmented Labor Market
segmented labor market unemployment trajectories Kohonenalgorithm Markov chain
2010/4/27
Using the Panel Study of Income Dynamics data on the period 1982-1992,
this paper investigates some mechanisms of the labor market in the United
States. This market is analyzed as a stable structure...