• The Korean Journal of Applied Statistics
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• v.22 no.1
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• pp.75-88
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• 2009

Gross Regional Domestic Product (GRDP) is regarded as an essential information to understand regional economy. However, GRDP is hardly used for establishment of regional economic plan and related statistical research due to its late and yearly publication. Therefore, it is necessary to estimate quarterly GRDP to grasp the current regional economy faster In this study, considering the comovement between GDP and GRDP for the same industry, reference series are made. Quarterly GRDP is estimated the following two steps; First, preliminary quarterly GRDP is estimated using Chow-Lin's method based on the reference series to eliminate temporal discrepancies. Second, preliminary quarterly GRDP is adjusted using Denton's multivariate method to eliminate contemporaneous discrepancies.

• Communications for Statistical Applications and Methods
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• v.25 no.2
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• pp.131-157
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• 2018

We propose a robust event date model to estimate the date of a target event by a combination of individual dates obtained from archaeological artifacts assumed to be contemporaneous. These dates are affected by errors of different types: laboratory and calibration curve errors, irreducible errors related to contaminations, and taphonomic disturbances, hence the possible presence of outliers. Modeling based on a hierarchical Bayesian statistical approach provides a simple way to automatically penalize outlying data without having to remove them from the dataset. Prior information on individual irreducible errors is introduced using a uniform shrinkage density with minimal assumptions about Bayesian parameters. We show that the event date model is more robust than models implemented in BCal or OxCal, although it generally yields less precise credibility intervals. The model is extended in the case of stratigraphic sequences that involve several events with temporal order constraints (relative dating), or with duration, hiatus constraints. Calculations are based on Markov chain Monte Carlo (MCMC) numerical techniques and can be performed using ChronoModel software which is freeware, open source and cross-platform. Features of the software are presented in Vibet et al. (ChronoModel v1.5 user's manual, 2016). We finally compare our prior on event dates implemented in the ChronoModel with the prior in BCal and OxCal which involves supplementary parameters defined as boundaries to phases or sequences.