TY - JOUR

T1 - Visualization of time series statistical data by shape analysis (GDP ratio changes among Asia countries)

AU - Shirota, Yukari

AU - Hashimoto, Takako

AU - Sari, Riri Fitri

N1 - Publisher Copyright:
© 2018 Published under licence by IOP Publishing Ltd.

PY - 2018/4/5

Y1 - 2018/4/5

N2 - It has been very significant to visualize time series big data. In the paper we shall discuss a new analysis method called "statistical shape analysis" or "geometry driven statistics" on time series statistical data in economics. In the paper, we analyse the agriculture, value added and industry, value added (percentage of GDP) changes from 2000 to 2010 in Asia. We handle the data as a set of landmarks on a two-dimensional image to see the deformation using the principal components. The point of the analysis method is the principal components of the given formation which are eigenvectors of its bending energy matrix. The local deformation can be expressed as the set of non-Affine transformations. The transformations give us information about the local differences between in 2000 and in 2010. Because the non-Affine transformation can be decomposed into a set of partial warps, we present the partial warps visually. The statistical shape analysis is widely used in biology but, in economics, no application can be found. In the paper, we investigate its potential to analyse the economic data.

AB - It has been very significant to visualize time series big data. In the paper we shall discuss a new analysis method called "statistical shape analysis" or "geometry driven statistics" on time series statistical data in economics. In the paper, we analyse the agriculture, value added and industry, value added (percentage of GDP) changes from 2000 to 2010 in Asia. We handle the data as a set of landmarks on a two-dimensional image to see the deformation using the principal components. The point of the analysis method is the principal components of the given formation which are eigenvectors of its bending energy matrix. The local deformation can be expressed as the set of non-Affine transformations. The transformations give us information about the local differences between in 2000 and in 2010. Because the non-Affine transformation can be decomposed into a set of partial warps, we present the partial warps visually. The statistical shape analysis is widely used in biology but, in economics, no application can be found. In the paper, we investigate its potential to analyse the economic data.

UR - http://www.scopus.com/inward/record.url?scp=85045734330&partnerID=8YFLogxK

U2 - 10.1088/1742-6596/971/1/012013

DO - 10.1088/1742-6596/971/1/012013

M3 - Conference article

AN - SCOPUS:85045734330

VL - 971

JO - Journal of Physics: Conference Series

JF - Journal of Physics: Conference Series

SN - 1742-6588

IS - 1

M1 - 012013

T2 - International Conference on Data and Information Science 2017, ICoDIS 2017

Y2 - 5 December 2017 through 6 December 2017

ER -