data_dippers: Capture-recapture data for European dippers

In wiqid: Quick and Dirty Estimates for Wildlife Populations

Capture-recapture data for European dippers

Description

A data set that accompanies Program MARK and is included in the RMark package in a different format under the name dipper.

Usage

data(dippers)

Format

A data frame with 294 observations on the following 8 variables.

Y1, Y2, Y3, Y4, Y5, Y6, Y7

detection histories for 294 dippers over 7 years: '1' if captured, '0' if not captured.

sex

sex of each bird captured.

Source

Lebreton, J-D; K P Burnham; J Clobert; D R Anderson. 1992. Modeling survival and testing biological hypotheses using marked animals: a unified approach with case studies. Ecological Monographs, 62, 67-118.

References

Analysis given in many books and papers, notably:

Cooch, E; G White 2014 (13th edition, but constantly updated). Program MARK: a gentle introduction. Available online in PDF format at: http://www.phidot.org/software/mark/docs/book/

Examples

data(dippers)

DH <- dippers[1:7]  # Extract the detection histories
survCJS(DH)  # the phi(.) p(.) model
survCJS(DH, phi ~ .time)  # the phi(t) p(.) model

# Floods affected the 2nd and 3rd intervals
df <- data.frame(flood = c(FALSE, TRUE, TRUE, FALSE, FALSE, FALSE))
survCJS(DH, phi ~ flood, data=df)

# Including a grouping factor:
survCJS(DH, phi ~ flood * group, data=df, group=dippers$sex)

# Bayesian estimation:


if(requireNamespace("rjags")) {
  Bdip <- BsurvCJS(DH, parallel=FALSE)
  plot(Bdip)
  BdipFlood <- BsurvCJS(DH, list(phi ~ flood, p ~ .time), data=df, parallel=FALSE)
  BdipFlood
  op <- par(mfrow=2:1)
  plot(BdipFlood, "phi[1]", xlim=c(0.3, 0.75), main="No flood")
  plot(BdipFlood, "phi[2]", xlim=c(0.3, 0.75), main="Flood")
  par(op)
  ratio <- BdipFlood['phi[2]'] / BdipFlood['phi[1]']
  postPlot(ratio, compVal=1)
}

wiqid documentation built on Nov. 18, 2022, 1:07 a.m.