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Distribution and interpolation using transformed data

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  • David Aadland

Abstract

This paper addresses the distribution and interpolation of time series that have been subject to various data transformations. Monte Carlo experiments are performed, which suggest that failure to account for these data transformations may lead to serious errors in estimation.

Suggested Citation

  • David Aadland, 2000. "Distribution and interpolation using transformed data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 27(2), pages 141-156.
    • Handle: RePEc:taf:japsta:v:27:y:2000:i:2:p:141-156
    DOI: 10.1080/02664760021682
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    Cited by:

    1. Baoline Chen, 2007. "An Empirical Comparison of Methods for Temporal Distribution and Interpolation at the National Accounts," BEA Papers 0077, Bureau of Economic Analysis.
    2. Elisa Keller, 2007. "Classical and Bayesian Methods for the VAR Analysis: International Comparisons," Rivista di Politica Economica, SIPI Spa, vol. 97(6), pages 149-202, November-.

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