Distribution and interpolation using transformed data

David Aadland ()

Journal of Applied Statistics, 2000, vol. 27, issue 2, pages 141-156

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.

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