Smoothing time-series data by nonmetric polytone curves

Adi Raveh; Gur Mosheiov

doi:10.1080/03610918808812677

Smoothing time-series data by nonmetric polytone curves

Adi Raveh, Gur Mosheiov

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Abstract

This paper suggests a simple nonmetric method for smoothing time series data. The smoothed series is the closest polytone curve to the presmoothed series in terms of least sum of absolute deviations. The method is exemplified on several seasonally adjusted series in order to estimate their trend component.

Original language	English
Pages (from-to)	515-536
Number of pages	22
Journal	Communications in Statistics Part B: Simulation and Computation
Volume	17
Issue number	2
DOIs	https://doi.org/10.1080/03610918808812677
State	Published - 1 Jan 1988

Bibliographical note

Funding Information:
This paper was written in part while the authors were at Baruch ~oll&e -- CUNY and Columbia University, respectively. Many thanks are due to E. Parzen and the referee for their fruitful comments. This work was supported, in part, by the Recanati Foundation.

Keywords

Monotone Curve
Polytone Curve
Seasonally-adjusted data
Trend component

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10.1080/03610918808812677

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KW - Seasonally-adjusted data

KW - Trend component

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Smoothing time-series data by nonmetric polytone curves

Abstract

Bibliographical note

Keywords

Access to Document

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