Time series interpolation via global optimization of moments fitting

Emilio Carrizosa, Alba V. Olivares-Nadal and Pepa Ramírez-Cobo

European Journal of Operational Research, 2013, vol. 230, issue 1, 97-112

Abstract: Most time series forecasting methods assume the series has no missing values. When missing values exist, interpolation methods, while filling in the blanks, may substantially modify the statistical pattern of the data, since critical features such as moments and autocorrelations are not necessarily preserved.

Keywords: Missing values; Moments matching; Global optimization; Variable Neighborhood Search (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:230:y:2013:i:1:p:97-112

DOI: 10.1016/j.ejor.2013.04.008

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