Bayesian Nonparametric Model for Estimating Multistate Travel Time Distribution
نویسندگان
چکیده
منابع مشابه
A Bayesian nonparametric Markovian model for non-stationary time series
Stationary time series models built from parametric distributions are, in general, limited in scope due to the assumptions imposed on the residual distribution and autoregression relationship. We present a modeling approach for univariate time series data, which makes no assumptions of stationarity, and can accommodate complex dynamics and capture non-standard distributions. The model for the t...
متن کاملA time dependent Bayesian nonparametric model for air quality analysis
Air quality monitoring is based on pollutants concentration levels, typically recorded in metropolitan areas. These exhibit spatial and temporal dependence as well as seasonality trends, and their analysis demands flexible and robust statistical models. Here we propose to model the measurements of particulate matter, composed by atmospheric carcinogenic agents, by means of a Bayesian nonparamet...
متن کاملEstimating E-Bayesian of Parameters of two parameter Exponential Distribution
In this study, E-Bayesian of parameters of two parameter exponential distribution under squared error loss function is obtained. The estimated and the efficiency of the proposed method has been compared with Bayesian estimator using Monte Carlo simulation.
متن کاملBayesian nonparametric predictions for count time series
In this paper we introduce a Bayesian nonparametric methodology for producing coherent predictions of count time series using the INAR(1) process. Our predictions are based on estimates of the p-step ahead predictive mass functions assuming a nonparametric prior for the distribution of the error term having large support on the space of discrete probability mass functions. An efficient Gibbs sa...
متن کاملA consistent nonparametric Bayesian procedure for estimating autoregressive conditional densities
This article proposes a Bayesian infinite mixture model for the estimation of the conditional density of an ergodic time series. A nonparametric prior on the conditional density is described through the Dirichlet process. In the mixture model, a kernel is used leading to a dynamic nonlinear autoregressivemodel. This model can approximate any linear autoregressivemodel arbitrarily closely while ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Advanced Transportation
سال: 2017
ISSN: 0197-6729,2042-3195
DOI: 10.1155/2017/5069824