विधियों की तुलना करें

	कैप्चर-रिकैप्चर जनसंख्या अनुमान	पॉइसन और ऋणात्मक द्विपद प्रतिगमन (Poisson and Negative Binomial Regression)
क्षेत्र	सर्वेक्षण पद्धति	अर्थमिति
परिवार	Regression model	Regression model
उद्भव वर्ष	1978	1998
प्रवर्तक	Otis, Burnham, White & Anderson	Cameron & Trivedi (textbook treatment); Hilbe (negative binomial)
प्रकार	Probabilistic population size estimator	Generalized linear model for count data
मौलिक स्रोत	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.	Cameron, A. C. & Trivedi, P. K. (1998). Regression Analysis of Count Data. Cambridge University Press.
उपनाम	Mark-Recapture, Tag-Recapture, Mark-Release-Recapture, İşaretle-Yeniden Yakala	count regression, log-linear count model, negative binomial regression, Poisson / Negatif Binom Regresyon
संबंधित	2	4
सारांश	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.