We consider the problem of population estimation using capture-recapture data, where capture probabilities can vary between sampling occasions and behavioural responses. The original model is not identifiable without ...We consider the problem of population estimation using capture-recapture data, where capture probabilities can vary between sampling occasions and behavioural responses. The original model is not identifiable without further restrictions. The novelty of this article is to expand the current research practice by developing a hierarchical Bayesian approach with the assumption that the odds of recapture bears a constant relationship to the odds of initial capture. A real-data example of deer mice population is given to illustrate the proposed method. Three simulation studies are developed to inspect the performance of the proposed Bayesian estimates. Compared with the maximum likelihood estimates discussed in Chao et al. (2000), the hierarchical Bayesian estimate provides reasonably better population estimation with less mean square error;moreover, it is sturdy to underline relationship between the initial and re-capture probabilities. The sensitivity study shows that the proposed Bayesian approach is robust to the choice of hyper-parameters. The third simulation study reveals that both relative bias and relative RMSE approach zero as population size increases. A R-package is developed and used in both data example and simulation.展开更多
Many studies have looked at how dogs respond to human communicative information. Here, we examined which human communicative factors were important in influencing dogs’ responses. Eleven healthy pet dogs with no appa...Many studies have looked at how dogs respond to human communicative information. Here, we examined which human communicative factors were important in influencing dogs’ responses. Eleven healthy pet dogs with no apparent aggressive behaviour toward people were recruited. Five sensory conditions (all cues presented;either a visual, an auditory, or an olfactory cue presented;no cues presented) were provided three times randomly to each dog during the tests. All tests were video recorded, and both the dogs’ behaviour and time taken to reach the person when she presented each of the sensory cue conditions were observed. Total rates of reaching the person were as follows: 97.0% (all cues), 87.9% (auditory cues), 84.4% (visual cues), 84.4% (olfactory cues), and 69.7% (no cues). The time taken for the dog to notice the person in the box and then obtain a reward from her differed among the five conditions: all cues (6.00 ± 0.32 s) and visual cues (6.02 ± 0.91 s) were significantly faster than auditory cues (18.56 ± 9.57 s) and no cues (26.55 ± 11.72 s). Thus the type of information input was important in recognition of the person by the dogs and influenced the dogs’ response times;visual cues appeared advantageous in confirming the person’s presence.展开更多
文摘We consider the problem of population estimation using capture-recapture data, where capture probabilities can vary between sampling occasions and behavioural responses. The original model is not identifiable without further restrictions. The novelty of this article is to expand the current research practice by developing a hierarchical Bayesian approach with the assumption that the odds of recapture bears a constant relationship to the odds of initial capture. A real-data example of deer mice population is given to illustrate the proposed method. Three simulation studies are developed to inspect the performance of the proposed Bayesian estimates. Compared with the maximum likelihood estimates discussed in Chao et al. (2000), the hierarchical Bayesian estimate provides reasonably better population estimation with less mean square error;moreover, it is sturdy to underline relationship between the initial and re-capture probabilities. The sensitivity study shows that the proposed Bayesian approach is robust to the choice of hyper-parameters. The third simulation study reveals that both relative bias and relative RMSE approach zero as population size increases. A R-package is developed and used in both data example and simulation.
文摘Many studies have looked at how dogs respond to human communicative information. Here, we examined which human communicative factors were important in influencing dogs’ responses. Eleven healthy pet dogs with no apparent aggressive behaviour toward people were recruited. Five sensory conditions (all cues presented;either a visual, an auditory, or an olfactory cue presented;no cues presented) were provided three times randomly to each dog during the tests. All tests were video recorded, and both the dogs’ behaviour and time taken to reach the person when she presented each of the sensory cue conditions were observed. Total rates of reaching the person were as follows: 97.0% (all cues), 87.9% (auditory cues), 84.4% (visual cues), 84.4% (olfactory cues), and 69.7% (no cues). The time taken for the dog to notice the person in the box and then obtain a reward from her differed among the five conditions: all cues (6.00 ± 0.32 s) and visual cues (6.02 ± 0.91 s) were significantly faster than auditory cues (18.56 ± 9.57 s) and no cues (26.55 ± 11.72 s). Thus the type of information input was important in recognition of the person by the dogs and influenced the dogs’ response times;visual cues appeared advantageous in confirming the person’s presence.
