Showing 1 - 10 of 97
Estimating a covariance matrix efficiently and discovering its structure are important statistical problems with applications in many fields. This article takes a Bayesian approach to estimate the covariance matrix of Gaussian data. We use ideas from Gaussian graphical models and model selection...
Persistent link: https://www.econbiz.de/10005135157
A method for constructing priors is proposed that allows the off-diagonal elements of the concentration matrix of Gaussian data to be zero. The priors have the property that the marginal prior distribution of the number of nonzero off-diagonal elements of the concentration matrix (referred to...
Persistent link: https://www.econbiz.de/10008861555
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This paper evaluates the performances of prediction intervals generated from alternative time series models, in the context of tourism forecasting. The forecasting methods considered include the autoregressive (AR) model, the AR model using the bias-corrected bootstrap, seasonal ARIMA models,...
Persistent link: https://www.econbiz.de/10010577317
This paper evaluates the performance of prediction intervals generated from alternative time series models, in the context of tourism forecasting. The forecasting methods considered include the autoregressive (AR) model, the AR model using the bias-corrected bootstrap, seasonal ARIMA models,...
Persistent link: https://www.econbiz.de/10005581119
This paper evaluates the performances of prediction intervals generated from alternative time series models, in the context of tourism forecasting. The forecasting methods considered include the autoregressive (AR) model, the AR model using the bias-corrected bootstrap, seasonal ARIMA models,...
Persistent link: https://www.econbiz.de/10009195106
This research examines how LCCs and airports develop their business relationships and the influences of power imbalance and mutual dependence on their interactions, as well as their relationship outcomes. Multiple case studies method was adopted in this research. Four LCC–airport relationships...
Persistent link: https://www.econbiz.de/10010662421
This paper demonstrates that the class of conditionally linear and Gaussian state-space models offers a general and convenient framework for simultaneously handling nonlinearity, structural change and outliers in time series. Many popular nonlinear time series models, including threshold, smooth...
Persistent link: https://www.econbiz.de/10004972268