A numerical nonmetric approach for analyzing time series data
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Summary
A numerical nonmetric approach to data analysis of periodic series with polytone trend is suggested and robustness of the proposed approach enables analysis of very short series, series with missing values, and other series with limitations that cannot be easily handled otherwise.
- Type
- article
- Published
- 1981-01-01
- Cited by
- 8
- References
- 8
- OpenAlex
- https://openalex.org/W2001630090
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:120509796
Keywords
Series (stratigraphy), Robustness (evolution), Monotone polygon, Time series, Computer science
References
- Seasonal Adjustment Based on a Mixed Additive‐Multiplicative Model
- The X-11 variant of the census method II seasonal adjustment program
- Minimizing a function without calculating derivatives
- A Survey of Time Series
- A Commentary on 'A Survey of Time Series'
- Statistical analysis of time series
- Moving Seasonal Adjustment of Economic Time Series
- AN EXPERIMENTAL LOOK AT SEASONAL ADJUSTMENT .~ COMPARATIVE STUDY OF ~N-INE ALTERNATIVE ADJUSTMENT METHODS
- The Statistical Analysis of Time Series.
Cited by
- Forecasting demand in international markets: The case of correlated time series
- Comments on Some Properties of X-11
- On trend estimation of time-series: a simple linear programming approach
- A NEW VERSION OF STRUCTURAL PERSISTENCE IN PREDICTION
- Smoothing time-series data by nonmetric polytone curves
- The chatfield-prothero case study: Another look
- Gini correlation as a measure of monotonicity and two of its usages
- On Measures of Monotone Association
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