hare: Snowshoe Hare Data

In Rcapture: Loglinear Models for Capture-Recapture Experiments

Snowshoe Hare Data

Description

This data set contains capture-recapture data for snowshoe hares.

Usage

hare

Format

68 by 6 numeric matrix, with the following columns:

c1, c2, c3, c4, c5, c6

Capture histories from the six capture occasions

Details

This data set is analyzed in Cormack (1989) and Agresti (1994).

Each row of this data set represents the capture history of one animal.

References

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), doi: 10.18637/jss.v019.i05.

Cormack, R. M. (1989) Loglinear models for capture-recapture. Biometrics, 45, 395–413.

Examples

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", h.control = list(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[rowSums(mat) == 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.

Rcapture documentation built on May 4, 2022, 5:05 p.m.