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| Model Rintangan untuk Data Hitungan× | Regresi Kuadrat Terkecil Biasa (Ordinary Least Squares - OLS)× | |
|---|---|---|
| Bidang≠ | Statistika | Ekonometrika |
| Keluarga | Regression model | Regression model |
| Tahun asal≠ | 1986 | 2019 |
| Pencetus≠ | Mullahy | Wooldridge (textbook treatment); classical least squares |
| Tipe≠ | Two-part count model | Linear regression |
| Sumber perintis≠ | Mullahy, J. (1986). Specification and Testing of Some Modified Count Data Models. Journal of Econometrics, 33(3), 341–365. DOI ↗ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Alias | hurdle count model, two-part count model, zero-truncated count model, Engel Modeli (Hurdle Model) | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Terkait | 5 | 5 |
| Ringkasan≠ | The hurdle model is a two-part count-data model introduced by Mullahy (1986). A first stage models the binary choice of crossing a hurdle (a zero versus a non-zero count), and a second stage models the strictly positive counts with a zero-truncated distribution such as a zero-truncated Poisson or negative binomial. | Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE). |
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