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timeseriesdb: Manage and Archive Time Series Data in Establishment Statistics with R and PostgreSQL

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    timeseriesdb is an R package which suggests a PostgreSQL database structure to store time series alongside extensive multi-lingual meta information and provides an R database interface including a web based GUI. The timeseriesdb package was designed to handle time series in establishment statistics. Information such as the GDP or data stemming from the aggregation of economic surveys is typically published on a monthly, quarterly or yearly basis. Hence the package is optimized to handle a large amount of dierent time series as opposed to managing a smaller number of high frequency time series such as real time data obtained from measuring devices. The particular focus of timeseriesdb is to help the user nd and extract a particular set of information within a larger set of information. The timeseriesdb package intends to provide the infrastructure for a time series catalog as opposed to handling time series operations on database level. The underlying structure relies on PostgreSQL's hstore data type which allows to store an array of key-value pairs in a single cell. The hstore data type is not only used to reduce the number of records by storing an entire time series in a single record but also to store a record specic amount of multi-lingual meta information items exibly.

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    Paper provided by KOF Swiss Economic Institute, ETH Zurich in its series KOF Working papers with number 15-384.

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    Length: 23 pages
    Date of creation: Jun 2015
    Handle: RePEc:kof:wpskof:15-384
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    1. B. D. McCullough & H. D. Vinod, 2003. "Verifying the Solution from a Nonlinear Solver: A Case Study," American Economic Review, American Economic Association, vol. 93(3), pages 873-892, June.
    2. Manik L. Shrestha & Marco Marini, 2013. "Quarterly GDP Revisions in G-20 Countries; Evidence from the 2008 Financial Crisis," IMF Working Papers 13/60, International Monetary Fund.
    3. Roger Koenker & Achim Zeileis, 2009. "On reproducible econometric research," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 833-847.
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