পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| MIDAS রিগ্রেশন: মিশ্র ডেটা ফ্রিকোয়েন্সির মধ্যে পূর্বাভাস× | ভেক্টর অটো রিগ্রেশন (VAR) মডেল× | |
|---|---|---|
| ক্ষেত্র | অর্থমিতি | অর্থমিতি |
| পরিবার | Regression model | Regression model |
| উদ্ভবের বছর≠ | 2007 | 2005 |
| প্রবর্তক≠ | Eric Ghysels, Arthur Sinko & Rossen Valkanov | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition |
| ধরন≠ | Parametric mixed-frequency forecasting model | Multivariate time-series model |
| মৌলিক উৎস≠ | Ghysels, E., Sinko, A., & Valkanov, R. (2007). MIDAS regressions: Further results and new directions. Econometric Reviews, 26(1), 53–90. DOI ↗ | Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗ |
| অপর নাম | Mixed Frequency Regression, Mixed Data Sampling Model, High-Frequency Forecasting Regression, MIDAS Regresyonu | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon |
| সম্পর্কিত≠ | 3 | 4 |
| সারসংক্ষেপ≠ | MIDAS (Mixed Data Sampling) Regression is an econometric framework that directly incorporates high-frequency predictors into models for lower-frequency outcome variables without requiring temporal aggregation of the regressors. Introduced by Eric Ghysels, Arthur Sinko, and Rossen Valkanov in 2007, MIDAS uses parsimoniously parameterized lag polynomials — such as the Beta or Exponential Almon weighting schemes — to summarize the information content of many high-frequency lags while avoiding parameter proliferation. | Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005). |
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