hare {Rcapture} | R Documentation |
This data set contains capture-recapture data for snowshoe hares.
data(hare)
68 by 6 numeric matrix, with the following columns:
c1
, c2
, c3
, c4
, c5
, c6
This data set is analysed in Cormack (1989) and Agresti (1994).
Each row of this data set represents the capture history of one animal.
Agresti, A. (1994) Simple capture-recapture models permitting unequal catchability and variable sampling effort. Biometrics, 50, 494–500.
Baillargeon, S. and Rivest, L.P. (2007) Rcapture: Loglinear models for capture-recapture in R. Journal of Statistical Software, 19(5), http://www.jstatsoft.org/v19/i05.
Cormack, R. M. (1989) Log-linear models for capture-recapture. Biometrics, 45, 395–413.
data(hare) desc<-descriptive(hare) plot(desc) # The fi plot shows that the two animals caught on all occasions create # some heterogeneity in the capture probabilities. closedp(hare) # The best fitting model Mth Poisson2(N = 81.1, s.e.=5.7) has an AIC of 146. closedpCI.t(hare,m="Mth",h="Poisson",theta=2) # One can compare the fit of this model with that obtained by removing the # 2 hares caught 6 times. This can be done by adding a column to the design # matrix for Mt taking the value 1 for the capture history (1,1,1,1,1,1). col<-rep(0,2^6-1) mat<-histpos.t(6) col[apply(mat,1,sum)==6]<-1 closedpCI.t(hare,mX=cbind(mat,col),mname="Mt without 111111") # This gives N = 76.8 (s.e.=3.9) with an AIC of 146.