Splines for annual temperature Data in India
| Vol-3 | Issue-06 | June 2018 | Published Online: 12 June 2018 PDF ( 220 KB ) | ||
| DOI: https://doi.org/10.5281/zenodo.1288683 | ||
| Author(s) | ||
A. Srinivasulu
1;
B. Sarojamma
2;
K. Anil kumar
3
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1Research Scholar, Department of Statistics, S.V.University, Tirupati, A.P. (India) 2Assistant professor, Department of Statistics, S.V.University, Tirupati, A.P. (India) 3Assistant professor, Department of Mathematics, GITAM University, Hyderabad, Telangana (India) |
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| Abstract | ||
Spline algorithms are the way to fit data points with a set of connecting curves (each one is called a Spline), such that the values between data points can be computed. They are various types/order of equations that can be used to specify the splines including Linear, Quadratic, Cubic, etc. Here annual temperature data is taken for 30 years from 1987 to 2016. In this data the highest temperature is in the year 1995, has structural break. So from 1987 to 1995 (9 years) we consider as before, and from 1996 to 2016 (21 years) consider as after. We applied four models such as Quadratic splines, Harmonic splines, Cubic splines and Regression splines for annual temperature data in India. In this paper We use Chow test for the presence of a structural break at a period. The four models are empirically tested using annual temperature data in India. |
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| Keywords | ||
| Annual Temperature data, Chow test, Cubic spline, Harmonic spline, Regression spline, Quadratic spline | ||
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Statistics
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