Modeling Space and Space-Time Directional Data Using Projected Gaussian Processes
نویسندگان
چکیده
Modeling Space and Space-Time Directional Data Using Projected Gaussian Processes Fangpo Wang & Alan E. Gelfand To cite this article: Fangpo Wang & Alan E. Gelfand (2014) Modeling Space and Space-Time Directional Data Using Projected Gaussian Processes, Journal of the American Statistical Association, 109:508, 1565-1580, DOI: 10.1080/01621459.2014.934454 To link to this article: http://dx.doi.org/10.1080/01621459.2014.934454
منابع مشابه
Dynamic Analysis of Multi-Directional Functionally Graded Panels and Comparative Modeling by ANN
In this paper dynamic analysis of multi-directional functionally graded panel is studied using a semi-analytical numerical method entitled the state-space based differential method (SSDQM) and comparative behavior modeling by artificial neural network (ANN) for different parameters. A semi-analytical approach which makes use the three-dimensional elastic theory and assuming the material propert...
متن کاملModeling Stock Return Volatility Using Symmetric and Asymmetric Nonlinear State Space Models: Case of Tehran Stock Market
Volatility is a measure of uncertainty that plays a central role in financial theory, risk management, and pricing authority. Turbulence is the conditional variance of changes in asset prices that is not directly observable and is considered a hidden variable that is indirectly calculated using some approximations. To do this, two general approaches are presented in the literature of financial ...
متن کاملAssessment of Effect Technical Directional Bremsstrahlung Splitting (DBS) on Spectra and Parameters of Simulation with Monte carlo Method BEAMnrc Code (Study Monte Carlo)
Introduction: Previous studies have shown that a Monte Carlo method for the transportations photon beam in medical linear accelerator is a good way. Strip of simulation can be used to measure the dose distribution in phantoms and patients' body. EGSnrc Code is the only code written for use in the field of radiation therapy that has many subset codes that BEAMnrc code is an impo...
متن کاملEvaluation and Application of the Gaussian-Log Gaussian Spatial Model for Robust Bayesian Prediction of Tehran Air Pollution Data
Air pollution is one of the major problems of Tehran metropolis. Regarding the fact that Tehran is surrounded by Alborz Mountains from three sides, the pollution due to the cars traffic and other polluting means causes the pollutants to be trapped in the city and have no exit without appropriate wind guff. Carbon monoxide (CO) is one of the most important sources of pollution in Tehran air. The...
متن کاملAnalysis of Hierarchical Bayesian Models for Large Space Time Data of the Housing Prices in Tehran
Housing price data is correlated to their location in different neighborhoods and their correlation is type of spatial (location). The price of housing is varius in different months, so they also have a time correlation. Spatio-temporal models are used to analyze this type of the data. An important purpose of reviewing this type of the data is to fit a suitable model for the spatial-temporal an...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2016