Võrdle meetodeid
Vaata valitud meetodeid kõrvuti; erinevad read on esile tõstetud.
| Püügi-tagasipüügi populatsiooni hindamine× | Poissoni ja negatiivse binomregressioon× | |
|---|---|---|
| Valdkond≠ | Küsitlusmetoodika | Ökonomeetria |
| Perekond | Regression model | Regression model |
| Tekkeaasta≠ | 1978 | 1998 |
| Looja≠ | Otis, Burnham, White & Anderson | Cameron & Trivedi (textbook treatment); Hilbe (negative binomial) |
| Tüüp≠ | Probabilistic population size estimator | Generalized linear model for count data |
| Algallikas≠ | Otis, D. L., Burnham, K. P., White, G. C., & Anderson, D. R. (1978). Statistical inference from capture data on closed animal populations. Wildlife Monographs, 62, 3–135. link ↗ | Cameron, A. C. & Trivedi, P. K. (1998). Regression Analysis of Count Data. Cambridge University Press. DOI ↗ |
| Rööpnimetused | Mark-Recapture, Tag-Recapture, Mark-Release-Recapture, İşaretle-Yeniden Yakala | count regression, log-linear count model, negative binomial regression, Poisson / Negatif Binom Regresyon |
| Seotud≠ | 2 | 4 |
| Kokkuvõte≠ | Capture-recapture (also known as mark-recapture) is a statistical method for estimating the size of an unknown population by sampling it twice and tracking which individuals appear in both samples. Formally systematized for closed animal populations by Otis, Burnham, White, and Anderson in their landmark 1978 Wildlife Monographs paper, the method extends naturally to human populations, epidemiology, and incomplete administrative records. | Poisson regression is a generalized linear model for count outcomes — events tallied as non-negative integers such as hospital admissions, accidents, or article counts. It models the log of the expected count as a linear function of the predictors, and is developed in the standard count-data treatment of Cameron and Trivedi (1998); when the counts are over-dispersed, the closely related negative binomial model (Hilbe, 2011) is preferred. |
| ScholarGateAndmestik ↗ |
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