print.openCR: Print or Summarise openCR Object

In MurrayEfford/openCR: Open Population Capture-Recapture

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	openCR object output from openCR.fit
object	openCR object output from openCR.fit
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 derived.openCR by summary.openCR

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

AIC.openCR, openCR.fit

Examples

## Not run: 

c1 <- openCR.fit(ovenCH, type='CJS', model=phi~session)
c1


## End(Not run)

MurrayEfford/openCR documentation built on Oct. 25, 2024, 8:06 a.m.