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Communications in Statistics - Simulation and Computation, ISSN 0361-0918, 10/2016, Volume 45, Issue 9, pp. 3238 - 3258
Bayesian inference for fractionally integrated exponential generalized autoregressive conditional heteroscedastic (FIEGARCH) models using Markov chain Monte... 
MCMC | Long-range dependence | Bayesian inference | FIEGARCH processes | 62F15; 62M10 | 62M10 | AUTOREGRESSIVE CONDITIONAL HETEROSKEDASTICITY | GIBBS SAMPLER | LONG-MEMORY | STATISTICS & PROBABILITY | VOLATILITY | 62F15 | Bayesian analysis | Monte Carlo simulation | Monte Carlo methods | Innovation | Parameters | Computer simulation | Markets | Mathematical models | Statistical methods
Journal Article
Communications in Statistics - Simulation and Computation, ISSN 0361-0918, 08/2019, Volume 48, Issue 7, pp. 2147 - 2164
Augmented mixed beta regression models are suitable choices for modeling continuous response variables on the closed interval [0, 1]. The random eeceeects in... 
Skew-normal Independent distribution | 62M10 | Beta regression model | MCMC algorithm | 62J05 | Augmented Beta distribution | Mixed models | 62F15 | STATISTICS & PROBABILITY | Parameter estimation | Regression models | Algorithms | Computer simulation | Skewed distributions | Regression analysis | Labor force | Labor | Bayesian analysis | Continuity (mathematics)
Journal Article
Bayesian Analysis, ISSN 1936-0975, 2011, Volume 6, Issue 1, pp. 145 - 178
Journal Article
Journal of Statistical Computation and Simulation, ISSN 0094-9655, 01/2019, Volume 89, Issue 1, pp. 71 - 97
Journal Article
Communications in Statistics - Simulation and Computation, ISSN 0361-0918, 10/2017, Volume 46, Issue 9, pp. 7008 - 7021
In this article, we consider a Bayesian analysis of a possible change in the parameters of autoregressive time series of known order p, AR(p). An unconditional... 
62M10 | Gibbs sampler | p-Values | Autoregressive model | Change point | HPD credible set | Bayesian analysis | 62F03 | 62F15 | P-values | DISTRIBUTIONS | TESTS | MODELS | STATISTICS & PROBABILITY | POINT | Change detection | Monte Carlo simulation | Time series | Autoregressive processes
Journal Article
Statistics, ISSN 0233-1888, 01/2018, Volume 52, Issue 1, pp. 34 - 49
In the regression analysis of time series of event counts, it is of interest to account for serial dependence that is likely to be present among such data as... 
62M10 | partial collapse | data-driven basis selection | Bayesian analysis | functional relationship | Poisson regression | 62F15 | BAYESIAN VARIABLE SELECTION | CALI | STATISTICS & PROBABILITY | LONGITUDINAL DATA | EFFICIENT ESTIMATION | COUNT TIME-SERIES | INFERENCES | COLOMBIA
Journal Article
Communications in Statistics - Theory and Methods, ISSN 0361-0926, 01/2017, Volume 46, Issue 1, pp. 296 - 318
In some fields, we are forced to work with missing data in multivariate time series. Unfortunately, the data analysis in this context cannot be carried out in... 
62M10 | marginal likelihood | Monte Carlo Markov chain | Bayesian analysis | metropolized Carlin-Chib | multivariate threshold autoregressive models | missing data | 62F15 | SERIES | MCMC | STATISTICS & PROBABILITY | Monte Carlo simulation | Markov analysis | Missing data | Thresholds | Time series | Strategy | Statistical methods | Statistics | Autoregressive processes
Journal Article
The Annals of Statistics, ISSN 0090-5364, 2/2014, Volume 42, Issue 1, pp. 64 - 86
Journal Article
Journal of Applied Statistics, ISSN 0266-4763, 03/2016, Volume 43, Issue 4, pp. 721 - 737
We use Bayesian methods to infer an unobserved function that is convolved with a known kernel. Our method is based on the assumption that the function of... 
62M10 | deconvolution | 62P30 | 35R30 | simulation | oil well test data | inverse problems | Gaussian processes | 62-07 | 62M09 | Bayesian inference | 62F15 | STATISTICS & PROBABILITY | MODEL | Oil wells | Bayesian analysis | Kernels | Correlation | Deconvolution | Applied statistics | Reservoirs | Gaussian
Journal Article
Communications in Statistics - Simulation and Computation, ISSN 0361-0918, 11/2017, Volume 46, Issue 10, pp. 7942 - 7956
In this article, we perform Bayesian estimation of stochastic volatility models with heavy tail distributions using Metropolis adjusted Langevin (MALA) and... 
Value at Risk | 62M10 | Langevin methods | Markov chain Monte Carlo | Metropolis-Hastings | Bayesian analysis | 62F15 | Metropolis–Hastings | Markov chain | Monte Carlo | MODELS | T-DISTRIBUTION | STATISTICS & PROBABILITY | Riemann manifold | Computer simulation | Mathematical analysis | Volatility | Monte Carlo simulation
Journal Article
Communications in Statistics - Simulation and Computation, ISSN 0361-0918, 08/2017, Volume 46, Issue 7, pp. 5285 - 5302
In this article, we propose to evaluate and compare Markov chain Monte Carlo (MCMC) methods to estimate the parameters in a generalized extreme value model. We... 
62M10 | Bayesian approach | Riemann manifold | Hamiltonian Monte Carlo | Extreme value | Markov chain Monte Carlo | 62F15 | STATISTICS & PROBABILITY | Monte Carlo method | Parameter estimation | Approximation | Computer simulation | Markov chains | Statistical inference | Bayesian analysis | Monte Carlo simulation | Extreme values | Statistics - Computation
Journal Article
Communications in Statistics - Simulation and Computation, ISSN 0361-0918, 08/2017, Volume 46, Issue 7, pp. 5440 - 5461
Journal Article
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, ISSN 0361-0926, 05/2014, Volume 43, Issue 10-12, pp. 2505 - 2515
Electricity market prices are highly volatile and often have high spikes. Both government authorities and market participants require sophisticated models and... 
62M10 | 60G35 | 62P20 | Price spike | Mean reversion | Seasonality | STATISTICS & PROBABILITY | Long memory | Forecasting | 93E11 | 91Bxx | 93E10 | Heteroskedasticity | 62F15 | 62M20 | 60G25
Journal Article
Communications in Statistics - Theory and Methods, ISSN 0361-0926, 08/2016, Volume 45, Issue 15, pp. 4332 - 4348
Journal Article
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS, ISSN 0361-0926, 05/2014, Volume 43, Issue 10-12, pp. 2505 - 2515
Electricity market prices are highly volatile and often have high spikes. Both government authorities and market participants require sophisticated models and... 
62M10 | 60G35 | 62P20 | Price spike | Mean reversion | Seasonality | STATISTICS & PROBABILITY | Long memory | Forecasting | 93E11 | 91Bxx | 93E10 | Heteroskedasticity | 62F15 | 62M20 | 60G25
Journal Article
Journal of Statistical Computation and Simulation, ISSN 0094-9655, 11/2016, Volume 86, Issue 16, pp. 3315 - 3336
Journal Article
Communications in Statistics - Simulation and Computation, ISSN 0361-0918, 03/2015, Volume 44, Issue 3, pp. 683 - 693
In this article, we assess Bayesian estimation and prediction using integrated Laplace approximation (INLA) on a stochastic volatility (SV) model. This was... 
62M10 | INLA | Bayesian methods | Quasi-maximum likelihood | 62F15 | Stochastic volatility models | STATISTICS & PROBABILITY | Volatility | Monte Carlo simulation | Stochastic models | Approximation | Computer simulation | Mathematical analysis | Time series | Mathematical models | Criteria | Bayesian analysis
Journal Article
Communications in Statistics - Theory and Methods, ISSN 0361-0926, 09/2014, Volume 43, Issue 18, pp. 3955 - 3985
Journal Article
Communications in Statistics - Theory and Methods, ISSN 0361-0926, 05/2014, Volume 43, Issue 10-12, pp. 2505 - 2515
Electricity market prices are highly volatile and often have high spikes. Both government authorities and market participants require sophisticated models and... 
91Bxx | Price spike | Mean reversion | Seasonality | Long memory | Heteroskedasticity | Forecasting | 62M10 | 60G35 | 62P20 | STATISTICS & PROBABILITY | 93E11 | 93E10 | 62F15 | 62M20 | 60G25 | Spikes | Monte Carlo methods | Computer simulation | Thresholds | Electricity pricing | Markets | Mathematical models | Statistics
Journal Article
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