A Bayesian conditional autoregressive geometric process model for range data

DOI10.1016/j.csda.2011.01.006zbMath1254.91642OpenAlexW2049746140MaRDI QIDQ1927087

S. T. Boris Choy, C. P. Y. Lam, Cathy W. S. Chen, Philip L. H. Yu, Jennifer So-Kuen Chan

Publication date: 30 December 2012

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2011.01.006

zbMATH Keywords

Bayesian analysisrange datageometric process\texttt{Winbugs}CARR model

Mathematics Subject Classification ID

Economic time series analysis (91B84)

Related Items (7)

Estimation of the parameters of the gamma geometric process ⋮ Efficient estimation of financial risk by regressing the quantiles of parametric distributions: an application to CARR models ⋮ Forecasting trade durations via ACD models with mixture distributions ⋮ Modelling and forecasting stock volatility and return: a new approach based on quantile Rogers-Satchell volatility measure with asymmetric bilinear CARR model ⋮ Multivariate generalized Poisson geometric process model with scale mixtures of normal distributions ⋮ Bayesian analysis of Cannabis offences using generalized Poisson geometric process model with flexible dispersion ⋮ Modeling Electricity Price Using A Threshold Conditional Autoregressive Geometric Process Jump Model

Uses Software

• WinBUGS
• BUGS

Cites Work

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• Statistical inference for geometric processes with gamma distributions
• Volatility forecasting using threshold heteroskedastic models of the intra-day range
• Estimation and inference for exponential smooth transition nonlinear volatility models
• Geometric processes and replacement problem
• Statistical inference for geometric processes with lognormal distribution.
• Hierarchical models with scale mixtures of normal distributions
• Generalized autoregressive conditional heteroscedasticity
• SCALE MIXTURES DISTRIBUTIONS IN STATISTICAL MODELLING
• Bayesian Modeling Using WinBUGS
• BAYESIAN THRESHOLD AUTOREGRESSIVE MODELS FOR NONLINEAR TIME SERIES
• Bayesian Measures of Model Complexity and Fit
• BAYESIAN INFERENCE OF THRESHOLD AUTOREGRESSIVE MODELS
• Equation of State Calculations by Fast Computing Machines
• Monte Carlo sampling methods using Markov chains and their applications
• Bayesian Model Selection for Join Point Regression with Application to Age-Adjusted Cancer Rates
• Fluctuation Theory of Recurrent Events

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