Maximum penalized likelihood estimation in semiparametric mark-recapture-recovery models

Michelot T, Langrock R, Kneib T, King R (2015)
Biometrical Journal 58(1): 222-239.

Zeitschriftenaufsatz | Veröffentlicht | Englisch
 
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Autor*in
Michelot, Théo; Langrock, RolandUniBi; Kneib, Thomas; King, Ruth
Erscheinungsjahr
2015
Zeitschriftentitel
Biometrical Journal
Band
58
Ausgabe
1
Seite(n)
222-239
ISSN
0323-3847
Page URI
https://pub.uni-bielefeld.de/record/2902628

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Michelot T, Langrock R, Kneib T, King R. Maximum penalized likelihood estimation in semiparametric mark-recapture-recovery models. Biometrical Journal. 2015;58(1):222-239.
Michelot, T., Langrock, R., Kneib, T., & King, R. (2015). Maximum penalized likelihood estimation in semiparametric mark-recapture-recovery models. Biometrical Journal, 58(1), 222-239. doi:10.1002/bimj.201400222
Michelot, Théo, Langrock, Roland, Kneib, Thomas, and King, Ruth. 2015. “Maximum penalized likelihood estimation in semiparametric mark-recapture-recovery models”. Biometrical Journal 58 (1): 222-239.
Michelot, T., Langrock, R., Kneib, T., and King, R. (2015). Maximum penalized likelihood estimation in semiparametric mark-recapture-recovery models. Biometrical Journal 58, 222-239.
Michelot, T., et al., 2015. Maximum penalized likelihood estimation in semiparametric mark-recapture-recovery models. Biometrical Journal, 58(1), p 222-239.
T. Michelot, et al., “Maximum penalized likelihood estimation in semiparametric mark-recapture-recovery models”, Biometrical Journal, vol. 58, 2015, pp. 222-239.
Michelot, T., Langrock, R., Kneib, T., King, R.: Maximum penalized likelihood estimation in semiparametric mark-recapture-recovery models. Biometrical Journal. 58, 222-239 (2015).
Michelot, Théo, Langrock, Roland, Kneib, Thomas, and King, Ruth. “Maximum penalized likelihood estimation in semiparametric mark-recapture-recovery models”. Biometrical Journal 58.1 (2015): 222-239.

1 Zitation in Europe PMC

Daten bereitgestellt von Europe PubMed Central.

Semi-Markov Arnason-Schwarz models.
King R, Langrock R., Biometrics 72(2), 2016
PMID: 26584064

43 References

Daten bereitgestellt von Europe PubMed Central.

Joint modelling of live recapture, tag-resight and tag-recovery data
Barker, Biometrics 53(), 1997
A class of latent marginal models for capture-recapture data with continuous covariates
Bartolucci, Journal of the American Statistical Association 101(), 2006
Integrating mark-recapture-recovery and census data to estimate animal abundance and demographic parameters.
Besbeas P, Freeman SN, Morgan BJ, Catchpole EA., Biometrics 58(3), 2002
PMID: 12229988
A Threshold Model for Heron Productivity
Besbeas P, Morgan BJT., Journal of agricultural, biological, and environmental statistics. 17(1), 2012
PMID: IND44760938

Bonner, 2009
Continuous covariates in mark-recapture-recovery analysis: a comparison of methods.
Bonner SJ, Morgan BJ, King R., Biometrics 66(4), 2010
PMID: 20163405

Boor, 1978
Capture-recapture studies for multiple strata including non-Markovian transitions
Hines, Biometrics 49(), 1993
Integrated recovery/recapture data analysis
Catchpole, Biometrics 54(), 1998
Abalone I: analyzing mark-recapture-recovery data incorporating growth and delayed recovery.
Catchpole EA, Freeman SN, Morgan BJ, Nash WJ., Biometrics 57(2), 2001
PMID: 11414571
A new method for analysing discrete life-history data with missing values
Catchpole, Journal of the Royal Statistical Society, Series B 70(), 2008

Efron, 1993
Flexible smoothing with B-splines and penalties
Eilers, Statistical Science 11(), 1996
Penalized structured additive regression for space-time data: a Bayesian perspective
Fahrmeir, Statistica Sinica 14(), 2004

Fewster, 2009
Semiparametric regression in capture-recapture modeling.
Gimenez O, Crainiceanu C, Barbraud C, Jenouvrier S, Morgan BJ., Biometrics 62(3), 2006
PMID: 16984309

Gimenez, 2009
Strictly proper scoring rules, prediction, and estimation
Gneiting, Journal of the American Statistical Association 102(), 2007
Flexible methods for analyzing survival data using splines, with application to breast cancer prognosis
Gray, Journal of the American Statistical Association 87(), 1992

King, 2009
Statistical ecology
King, Annual Review of Statistics and its Application 1(), 2014

AUTHOR UNKNOWN, 0
Simultaneous confidence bands for penalized spline estimators
Krivobokova, Journal of the American Statistical Association 105(), 2010
Maximum likelihood estimation of mark-recapture-recovery models in the presence of continuous covariates
Langrock, Annals of Applied Statistics 7(), 2013
Nonparametric inference in hidden Markov models using P-splines.
Langrock R, Kneib T, Sohn A, DeRuiter SL., Biometrics 71(2), 2015
PMID: 25586063

AUTHOR UNKNOWN, 0
The BTO heronries census of England and Wales 1928-2000: new indices and a comparison of analytical methods
Marchant, Ibis 146(), 2004

AUTHOR UNKNOWN, 0
Modeling heron survival using weather data
North, Biometrics 35(), 1979
Open capture-recapture models with heterogeneity: I. Cormack-Jolly-Seber model.
Pledger S, Pollock KH, Norris JL., Biometrics 59(4), 2003
PMID: 14969456

Pledger, 2009
Estimating migration rates using tag-recovery data
Schwarz, Biometrics 49(), 1993
A review of estimating animal abundance III
Schwarz, Statistical Science 14(), 2000
A robust P-spline approach to closed population capture-recapture models with time dependence and heterogeneity
Stoklosa, Computational Statistics and Data Analysis 56(), 2012

Ruppert, 2003
Capture-recapture smooth estimation of age-specific survival probabilities in animal populations
Viallefont, Journal of Agricultural, Biological and Environmental Statistics 16(), 2010
Analysing Mark–Recapture–Recovery Data in the Presence of Missing Covariate Data Via Multiple Imputation
Worthington H, King R, Buckland ST., Journal of agricultural, biological, and environmental statistics. 20(1), 2015
PMID: IND601243167

Zucchini, 2009
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