1999
DOI: 10.1111/j.0006-341x.1999.01263.x
|View full text |Cite
|
Sign up to set email alerts
|

Estimating Equations for Removal Data Analysis

Abstract: We consider the problem of estimating a population size from successive catches taken during a removal experiment and propose two estimating functions approaches, the traditional quasi-likelihood (TQL) approach for dependent observations and the conditional quasi-likelihood (CQL) approach using the conditional mean and conditional variance of the catch given previous catches. Asymptotic covariance of the estimates and the relationship between the two methods are derived. Simulation results and application to t… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

0
4
0

Year Published

2001
2001
2014
2014

Publication Types

Select...
4
3

Relationship

0
7

Authors

Journals

citations
Cited by 9 publications
(4 citation statements)
references
References 22 publications
(24 reference statements)
0
4
0
Order By: Relevance
“…There is also a range of methods for obtaining interval estimates for the population size (e.g., Schnute 1983;Harding et al 1984;Hirst 1994). When large numbers of passes are undertaken, it is possible to apply more realistic statistical models that allow for a systematic decline in capture probability between passes (Schnute 1983), random variation in capture probability between passes (Wang and Loneragan 1996;Wang 1999), and random variation in capture probability between individual fish (Lee and Chao 1994;Chao and Chang 1999).…”
Section: Introductionmentioning
confidence: 99%
“…There is also a range of methods for obtaining interval estimates for the population size (e.g., Schnute 1983;Harding et al 1984;Hirst 1994). When large numbers of passes are undertaken, it is possible to apply more realistic statistical models that allow for a systematic decline in capture probability between passes (Schnute 1983), random variation in capture probability between passes (Wang and Loneragan 1996;Wang 1999), and random variation in capture probability between individual fish (Lee and Chao 1994;Chao and Chang 1999).…”
Section: Introductionmentioning
confidence: 99%
“…Principal methods for analyzing removal data include regression of the catch against the cumulative catch (Leslie & Davis 1939; DeLury 1947; Ricker 1975), a multinomial model with maximum likelihood estimation (Carle & Strub 1978; Schnute 1983; Gould & Pollock 1997) and estimating functions/equations (e.g. Chao & Chang 1999; Wang 1999), using both frequentist and Bayesian approaches (e.g. Wyatt 2002).…”
Section: Methods and Resultsmentioning
confidence: 99%
“…1 and estimating equations were used in Ref. 46. Sampling probabilities have also been modeled [47] as linear logistic functions of covariates (see Logistic regression) in addition to effort.…”
Section: Catch-effortmentioning
confidence: 99%