Ferramenta para análise de séries temporais
Abstract
Time series analysis plays a key role in various sectors of society, its applications variate from forecasts on the stock exchange to detection of credit card fraud. This theme is part of the curriculum of several Higher Education courses, such as Computer Science, Agronomy, Statistics and other related courses. There is a problem regarding the tools used for the analysis of time series in most of these courses, such as the use of R, Python or Excel tools. When used, they generate a relatively high learning curve. In this context, this paper presents and analyze Metanalysis. A simple tool that facilitates the analysis of time series, providing a user-friendly interface.References
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Benesty, J., Chen, J., Huang, Y., and Cohen, I. (2009). Pearson correlation coefficient. In Noise reduction in speech processing, pages 1–4. Springer.
Cryer, J. D. and Kellet, N. (1991). Time series analysis. Springer.
Ehlers, R. S. (2007). Análise de séries temporais. Universidade Federal do Paraná.
Frigge, M., Hoaglin, D. C., and Iglewicz, B. (1989). Some implementations of the boxplot. The American Statistician, 43(1):50–54.
Garrard, C., Gerrity, T., Schreiner, J., and Yeates, D. (1981). The characterization of radioaerosol deposition in the healthy lung by histogram distribution analysis. Chest, 80(6 Suppl):840–842.
Hutcheson, G. D. (2011). Ordinary least-squares regression. L. Moutinho and GD Hutcheson, The SAGE dictionary of quantitative management research, pages 224–228.
Koehler, A. B., Snyder, R. D., and Ord, J. K. (2001). Forecasting models and prediction intervals for the multiplicative holt–winters method. International Journal of Forecasting, 17(2):269–286.
Koskela, T., Lehtokangas, M., Saarinen, J., and Kaski, K. (1996). Time series prediction with multilayer perceptron, fir and elman neural networks. In Proceedings of the World Congress on Neural Networks, pages 491–496. Citeseer.
MARolA, K., KBNT, J., and Bibly, J. (1979). Multivariate analysis. AcadeInic Press, Londres.
Paunzen, E. and Vanmunster, T. (2016). Peranso–light curve and period analysis software. Astronomische Nachrichten, 337(3):239–245.
Seber, G. A. and Lee, A. J. (2012). Linear regression analysis, volume 329. John Wiley & Sons.
Shibata, R. (1976). Selection of the order of an autoregressive model by akaike’s information criterion. Biometrika, 63(1):117–126.
Sivo, S. A. (2001). Multiple indicator stationary time series models. Structural Equation Modeling, 8(4):599–612.
Van Camp, M. and Vauterin, P. (2005). Tsoft: graphical and interactive software for the analysis of time series and earth tides. Computers & Geosciences, 31(5):631–640.
Van Der Aalst, W. (2016). Data science in action. In Process mining, pages 3–23. Springer.
Welch, H. L. and Seem, J. E. (2005). System and method for filling gaps of missing data using source specified data. US Patent 6,862,540.
Published
2020-10-26
How to Cite
DA CONCEIÇÃO, Jam Sávio; DOS SANTOS, Jadson Lúcio; CAVALCANTE, Rodolfo.
Ferramenta para análise de séries temporais. In: REGIONAL SCHOOL ON COMPUTING OF BAHIA, ALAGOAS, AND SERGIPE (ERBASE), 20. , 2020, Arapiraca-AL.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 272-281.
