Vecctor autoregrressive (VARR) process is common ttool for captturing the auutocorrelation pattern among Vstudy, bivariate coinexaminee the finite sadifferentt?^ and ?^ample perforrmance of esin MATLABstimators corrresponding to the asympptotic distribution for different P and a in MATLAB R2011A software package.
📌 3 Key Takeaways
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Objective & Hypothesis:Vecctor autoregrressive (VARR) process is common ttool for captturing the auutocorrelation pattern among Vstudy, bivariate coinexaminee the finite sadifferentt?^ and ?^ample perforrmance of esin MATLABstimators corrresponding to the asympptotic distribution for different P and a in MATLAB R2011A software package.
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Key Findings & Data:Vecctor autoregrressive (VARR) process is common ttool for captturing the auutocorrelation pattern among Vstudy, bivariate coinexaminee the finite sadifferentt?^ and ?^ample perforrmance of esin MATLABstimators corrresponding to the asympptotic distribution for different P and a in MATLAB R2011A software package.
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Conclusion & Impact:Vecctor autoregrressive (VARR) process is common ttool for captturing the auutocorrelation pattern among Vstudy, bivariate coinexaminee the finite sadifferentt?^ and ?^ample perforrmance of esin MATLABstimators corrresponding to the asympptotic distribution for different P and a in MATLAB R2011A software package.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters
Abstract
Vecctor autoregrressive (VARR) process is common ttool for captturing the auutocorrelation pattern among Vstudy, bivariate coinexaminee the finite sadifferentt?^ and ?^ample perforrmance of esin MATLABstimators corrresponding to the asympptotic distribution for different P and a in MATLAB R2011A software package.
Özet
Tek değişkenli otoregresif sürecin genelleştirilmiş hali olan vektör otoregresif süreç değişkenler arasında otokorelasyon örneklerini modelleyerek yaygınca kullanılan bir süre çtir.Çalışmamızda ikideğişkenli birinci dereceden vektör otoregresif süreç göz önüne alınmıştır. Monte Carlo simulasyonu yardımıyla ekran_al305nt305s305_53_01^ nın sonlu örneklem tahmin edicilerinin asismptotik özellikleri MATLABR2011A programı kullanılarak incelenmiştir.
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Cite This Article
FİRUZAN, E., SUSAM, S. (2022). İki Değişkenli Eşbütünleşik Var (1) Sürecinin Parametrelerinin Özellikleri. Anadolu Üniversitesi Bilim ve Teknoloji Dergisi :A-Uygulamalı Bilimler ve Mühendislik, Cilt: 14 - Sayı: 3, 263–276. https://ajindex.com/articles/438394
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