Abstract
The main interest of this paper is to state a new method which allows to adjust the statistical difficulty when the statistical series are spliced. Hence, we study the scope of different splicing methods in the literature. We present an approximation method for statistical splicing of economic data by using smoothing quadratic splines. Finally, we show the effectiveness of our method by presenting a complete data of Gross Domestic Product for Venezuela by productive economic activity from 1950 to 2005, expressed at prices of the base year of 1997, also by showing the results of some data of Morocco for different economics activities such as the Gross Domestic Product, the agriculture, the trade and the electricity generation from petroleum sources of Morocco between 1971 and 2015.
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Akhrif, R., Delgado-Márquez, E., Kouibia, A., Pasadas, M. (2022). Economic Statistical Splicing Data Using Smoothing Quadratic Splines. In: Barrera, D., Remogna, S., Sbibih, D. (eds) Mathematical and Computational Methods for Modelling, Approximation and Simulation. SEMA SIMAI Springer Series, vol 29. Springer, Cham. https://doi.org/10.1007/978-3-030-94339-4_8
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DOI: https://doi.org/10.1007/978-3-030-94339-4_8
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