چکیده مقاله
Recent technological advances have led to the appearance of high dimensional and complex datasets Functional data analysis is one of the most commonly used techniques in modeling such complex datasets This article introduces some functional methods to fit a functional regression model on the interval valued functional data Fourier basis system is considered for estimating the model parameters In the first proposed method, a functional linear regressionmodel is fitted based on the midpoints of the intervals The second method involves two independent functional linear models on the midpoint and the half range of the intervals Furthermore, the third method is based on a combination of the midpoint and the half range of intervals The applicability and advantages of the proposed models are investigated through a real data example
کلیدواژهها
نویسندگان
Zohreh Mohammadi
Department of Statistics, Jahrom University, Jahrom, Iran
Fariba Nasirzadeh
Department of Statistics, Jahrom University, Jahrom, Iran
Roya Nasirzadeh
Department of Statistics, Fasa University, Fasa, Iran
شیوه ارجاع
Mohammadi, Zohreh and Nasirzadeh, Fariba and Nasirzadeh, Roya,1400,Complex Data Analysis: modeling of interval-valued functional Data,Fourth International Conference on Soft Computing
ارائهشده در
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