Estimation of Nonorthogonal Problem Using Time Series Dataset

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200%">


200%">Abstract


200%">Based on presentation of the principles of nonorthogonal problem, we discuss the difference of some approaches. A simple procedure to include the R-squared and Root Mean Square Error (R.M.S.E) is proposed and tested. The results showed that the Partial Least Square Regression provides better predictions due to a small R.M.S.E value.


200%">Keyword. Nonorthogonal, Mean Square, Partial Least Square, R Square.


200%">


200%">Table of Content


200%">1.0 Introduction


200%">2.0 The Ordinary Least Square Model


200%">2.3 Ridge Regression (RR).


200%">3.0 Result and Discussion


200%">3.1 Illustrative Example


200%">4.0 Conclusion


200%">4.1 Recommendation


200%">Reference


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APA

BARTHOLOMEW, D. (2018). Estimation of Nonorthogonal Problem Using Time Series Dataset. Afribary. Retrieved from https://afribary.com/works/estimation-of-nonorthogonal-problem-using-time-series-dataset-3649

MLA 8th

BARTHOLOMEW, DESMOND "Estimation of Nonorthogonal Problem Using Time Series Dataset" Afribary. Afribary, 29 Jan. 2018, https://afribary.com/works/estimation-of-nonorthogonal-problem-using-time-series-dataset-3649. Accessed 24 May. 2022.

MLA7

BARTHOLOMEW, DESMOND . "Estimation of Nonorthogonal Problem Using Time Series Dataset". Afribary, Afribary, 29 Jan. 2018. Web. 24 May. 2022. < https://afribary.com/works/estimation-of-nonorthogonal-problem-using-time-series-dataset-3649 >.

Chicago

BARTHOLOMEW, DESMOND . "Estimation of Nonorthogonal Problem Using Time Series Dataset" Afribary (2018). Accessed May 24, 2022. https://afribary.com/works/estimation-of-nonorthogonal-problem-using-time-series-dataset-3649