An enhanced version of the SSA-HJ-biplot for time series with complex structure

Alberto Silva () and Adelaide Freitas ()
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Alberto Silva: University of Aveiro, Campus de Santiago
Adelaide Freitas: University of Aveiro, Campus de Santiago

Advances in Data Analysis and Classification, 2024, vol. 18, issue 2, No 8, 409-430

Abstract: Abstract HJ-biplots can be used with singular spectral analysis to visualize and identify patterns in univariate time series. Named SSA-HJ-biplots, these graphs guarantee the simultaneous representation of the trajectory matrix’s rows and columns with maximum quality in the same factorial axes system and allow visualization of the separation of the time series components. Structural changes in the time series can make it challenging to visualize the components’ separation and lead to erroneous conclusions. This paper discusses an improved version of the SSA-HJ-biplot capable of handling this type of complexity. After separating the series’ signal and identifying points where structural changes occurred using multivariate techniques, the SSA-HJ-biplot is applied separately to the series’ homogeneous intervals, which is why some improvement in the visualization of the components’ separation is intended.

Keywords: Structural change detection; Singular spectrum analysis; NIPALS algorithm; Biplots; 62H99 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11634-023-00541-x

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