Regresi Median Pada Copula Bivariat
DOI:
https://doi.org/10.31764/jtam.v3i1.728Keywords:
Analisis Regresi, Copula, Kurva Kuantil Bersyarat, Regresi MedianAbstract
Abstrak: Analisis regresi adalah analisis yang sering digunakan dalam segala bidang yang bertujuan untuk memodelkan hubungan antara dua jenis variabel tak bebas dengan satu atau variabel bebas. Regresi linier masih memiliki beberapa kekurangan, maka dari untuk mengatasinya dengan regresi median. Copula dapat digunakan untuk mendeteksi hubungan data bivariat dengan peubah-peubah yang berbeda. Hasil penelitian menunjukkan kurva kuantil bersyarat terbaik berdasarkan MSE terkecil Data I yaitu copula Plackett sebesar 0.8650. Sedangkan nilai MSE terkecil Data II yaitu copula Gaussian sebesar 0.3954. Nilai MSE terkecil Data III yaitu copula Frank sebesar 0.5575. Terakhir, nilai MSE terkecil Data IV yaitu copula Clayton sebesar 0.3190.
Abstract: Â Regression analysis is an analysis that is often used in all fields which aims to model the relationship between two types of non-dependent variables with one or independent variables. Linear regression still has several drawbacks, so to overcome this by median regression. Copula can be used to detect bivariate data relations with different variables. The results showed that the best conditional curves based on the smallest MSE of Data I were Plackett copula of 0.8650. While the smallest MSE value is Data II, which is a Gaussian population of 0.3954. The smallest MSE value of Data III is Frank copula of 0.5575. Finally, the smallest MSE value is Data IV which is copula Clayton of 0.3190.
References
Arisandi, N.L., Nugroho, D.B., dan Sasongko, L.R. (2018). Analisis Prediktif Berdasarkan Kurs Beli IDR-USD Melalui Regresi Copula, Jurnal Matematika dan Aplikasi deCartesian, 7(2).
Bernard, C and Czado, C. (2014). Conditional Quantiles and Tails Dependence.Journal Education and Behavior Stattistic, 2(1), 8-12.
Bertsekas DP, Tsitsiklis JN. (2008). Introduction to Probability 1nd Edition. New York: Athena Scientific.
Bhat, C.R and Eluru, N. (2009). Procedure to Generate Uniform Random Variates from Each Copula. Austin:University Station.
Luxviantono, E., Mahatma, T., dan Sasongko, L.R. (2018). Analisis Hubungan IHK (Indeks Harga Konsumen) dan Kurs Beli IDR-USD Melalui Pendekatan Copula. Jurnal Cartesian, 7(2).
Nelsen, R.B. (2006): An Introduction to Copulas 2nd Edition, New York: Springer Series in statistics USA.
Sasongko, L.R. (2014).Copula Untuk Memodelkan Kegagalan Dua Dimensi pada Produk Bergaransi dengan Strategi Penggantian. Tesis, Institut Teknologi Bandung
Tse, Y.K. (2009): Nonlife Actuarial Models: Theory, Methods & Evaluation, Cambridge Univesity Press.
Uthami, I.A.P, Sukarsa, I.G.K, dan Kencana, I.P.E.N. (2013). Regresi Kuantil Median untuk Mengatasi Heteroskedastisitas Pada Analisis Regresi. e-Jurnal Matematika,2(1).
Downloads
Published
Issue
Section
License
Authors who publish articles in JTAM (Jurnal Teori dan Aplikasi Matematika) agree to the following terms:
- Authors retain copyright of the article and grant the journal right of first publication with the work simultaneously licensed under a CC-BY-SA or The Creative Commons Attribution–ShareAlike License.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
