print.openCR {openCR} | R Documentation |
Print or Summarise openCR Object
Description
Print results from fitting a spatially explicit capture–recapture model, or generate a list of summary data.
Usage
## S3 method for class 'openCR'
print(x, newdata = NULL, alpha = 0.05, svtol = 1e-5,...)
## S3 method for class 'openCR'
summary(object, newdata = NULL, alpha = 0.05, svtol = 1e-5, deriv = FALSE, ...)
Arguments
x |
|
object |
|
newdata |
optional dataframe of values at which to evaluate model |
alpha |
alpha level |
svtol |
threshold for non-null eigenvalues when computing numerical rank |
deriv |
logical; if TRUE then table of derived parameters is calculated |
... |
other arguments passed to |
Details
Results are potentially complex and depend upon the analysis (see below). Optional newdata
should be a dataframe with a column for each of the variables in the model. If newdata
is missing then a dataframe is constructed automatically. Default newdata
are for a naive animal on the first occasion; numeric covariates are set to zero and factor covariates to their base (first) level. Confidence intervals are 100 (1 – alpha) % intervals.
call | the function call |
time | date and time fitting started |
N animals | number of distinct animals detected |
N captures | number of detections |
N sessions | number of sampling occasions |
Model | model formula for each `real' parameter |
Fixed | fixed real parameters |
N parameters | number of parameters estimated |
Log likelihood | log likelihood |
AIC | Akaike's information criterion |
AICc | AIC with small sample adjustment (Burnham and Anderson 2002) |
Beta parameters | coef of the fitted model, SE and confidence intervals |
Eigenvalues | scaled eigenvalues of Hessian matrix (maximum 1.0) |
Numerical rank | number of eigenvalues exceeding svtol |
vcov | variance-covariance matrix of beta parameters |
Real parameters | fitted (real) parameters evaluated at base levels of covariates |
AICc is computed with the default sample size (number of individuals) and parameter count (use.rank = FALSE).
Value
The summary
method constructs a list of outputs similar to those printed by the print
method,
but somewhat more concise and re-usable:
versiontime | secr version, and date and time fitting started |
traps* | detector summary |
capthist | capthist summary (primary and secondary sessions, numbers of animals and detections) |
intervals | intervals between primary sessions |
mask* | mask summary |
modeldetails | miscellaneous model characteristics (type etc.) |
AICtable | single-line output of AIC.openCR |
coef | table of fitted coefficients with CI |
predicted | predicted values (`real' parameter estimates) |
derived | output of derived.openCR (optional) |
* spatial models only
References
Burnham, K. P. and Anderson, D. R. (2002) Model selection and multimodel inference: a practical information-theoretic approach. Second edition. New York: Springer-Verlag.
See Also
Examples
## Not run:
c1 <- openCR.fit(ovenCH, type='CJS', model=phi~session)
c1
## End(Not run)