EKONOMETRIKADAGI INNOVATSION YECHIMLAR
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Innovatsion yechimlar, Ekonometrika, Mashinani o‘rganish, Sun’iy intellekt, Katta ma’lumotlar, Bayes usullari, Vaqt qatori tahlili, Muntazamlashtirish usullari, LASSO, Ridge regressiya, Elastic Net, R dasturi, Python dasturi, glmnet paketi, bsts paketi, scikit-learn kutubxonasi, MATLAB, Stata, EViews, Model integratsiyasi, Statistik tahlil, Prognozlash, Ma’lumotlar tahlili, Panel ma’lumotlar, Korrelyatsiya tahlili.Abstrak
Maqolada ekonometrika fanini o‘qitishda zamonaviy axborot texnologiyalaridan foydalanish orqali dars samaradorligini oshirish masalalari chuqur tahlil qilinadi. Xususan, Matrixer 5.1 dasturi yordamida korrelyatsiya va regressiya tahlillarini amalga oshirish bo‘yicha amaliy misollar keltiriladi. Shuningdek, GeoGebra va MS Excel dasturlarining iqtisodiy masalalarni yechishda qo‘llanilishi batafsil ko‘rib chiqiladi. Maqolada zamonaviy dasturlarni o‘quv jarayonida qo‘llashning afzalliklari, talabalarning axborot madaniyatini oshirishdagi ahamiyati va o‘qituvchilarning kompyuter dasturlari bilan ishlash malakalarini rivojlantirish zarurligi yoritilgan.
Iqtiboslar
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Banbura, M., Giannone, D., & Reichlin, L. (2010). "Large Bayesian Vector Auto Regressions." Journal of Applied Econometrics, 25(1), 71-92. https://doi.org/10.1002/jae.1137
Korobilis, D., & Pettenuzzo, D. (2020). "Machine Learning Econometrics: Bayesian Algorithms and Methods." arXiv preprint arXiv:2004.11486. https://arxiv.org/abs/2004.11486
Chan, F., & Mátyás, L. (Eds.). (2022). Econometrics with Machine Learning. Springer. https://doi.org/10.1007/978-3-031-15149-1
Kreinovich, V., Sriboonchitta, S., & Yamaka, W. (Eds.). (2024). Machine Learning for Econometrics and Related Topics. Springer. https://doi.org/10.1007/978-3-031-43601-7
Bauwens, L., & Lubrano, M. (1999). Bayesian Inference in Dynamic Econometric Models. Oxford University Press. https://doi.org/10.1093/0198773120.001.0001
Giannone, D., Lenza, M., & Primiceri, G. E. (2015). "Prior Selection for Vector Autoregressions." Review of Economics and Statistics, 97(2), 436-451. https://doi.org/10.1162/REST_a_00483
Hastie, T., Tibshirani, R., & Friedman, J. (2009). The Elements of Statistical Learning: Data Mining, Inference, and Prediction (2nd ed.). Springer. https://doi.org/10.1007/978-0-387-84858-7
