Original scientific paper
https://doi.org/10.1080/1331677X.2017.1305772
An investigation of export–import ratios in Turkey using spline regression models
Ömer Alkan
Erkan Oktay
Aşır Genç
Ali Kemal Çelik
Abstract
This paper examines the use of spline functions in linear, squared, and
cubic spline regression models and exhibits the estimation of spline
parameters from data by ordinary least squares. Determination of
the number and the location of knots is central to spline regression.
In this paper, we initially propose a method based on the coefficient
of determination R2 related to the estimation of knots in spline
regression. This proposed method as applied to export–import
ratio distributions in Turkey for the years 1923–2010 determines the
knots, and linear, quadratic, and cubic spline regression models are
established accordingly. Results reveal that spline regression models
offer better results than polynomial regression models, and that the
quadratic spline regression model is the best explanatory model for
export–import ratio distributions in the smoothest spline regression
models.
Keywords
Export–import ratio; spline regression; knot; export; import
Hrčak ID:
180813
URI
Publication date:
1.12.2017.
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