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print.secr

Print or Summarise secr Object


Description

Print results from fitting a spatially explicit capture–recapture model or generate a list of summary values.

Usage

## S3 method for class 'secr'
 print(x, newdata = NULL, alpha = 0.05, deriv = FALSE, call = TRUE, ...)
## S3 method for class 'secr'
 summary(object, newdata = NULL, alpha = 0.05, deriv = FALSE, ...)

Arguments

x

secr object output from secr.fit

object

secr object output from secr.fit

newdata

optional dataframe of values at which to evaluate model

alpha

alpha level

deriv

logical for calculation of derived D and esa

call

logical; if TRUE the call is printed

...

other arguments optionally passed to derived.secr

Details

Results from print.secr 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 (optional)
version,time secr version, date and time fitting started, and elapsed time
Detector type `single', `multi', `proximity' etc.
Detector number number of detectors
Average spacing
x-range
y-range
New detector type as fitted when details$newdetector specified
N animals number of distinct animals detected
N detections number of detections
N occasions number of sampling occasions
Mask area
Model model formula for each `real' parameter
Fixed (real) fixed real parameters
Detection fn detection function type (halfnormal or hazard-rate)
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
vcov variance-covariance matrix of beta parameters
Real parameters fitted (real) parameters evaluated at base levels of covariates
Derived parameters derived estimates of density and mean effective sampling area (optional)

Derived parameters (see derived) are computed only if deriv = TRUE.

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
mask mask summary
modeldetails miscellaneous model characteristics (CL etc.)
AICtable single-line output of AIC.secr
coef table of fitted coefficients with CI
predicted predicted values (`real' parameter estimates)
derived output of derived.secr (optional)

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

## load & print previously fitted null (constant parameter) model
print(secrdemo.0)

summary(secrdemo.0)

## combine AIC tables from list of summaries
do.call(AIC, lapply(list(secrdemo.b, secrdemo.0), summary))

## Not run: 

print(secrdemo.CL, deriv = TRUE)


## End(Not run)

secr

Spatially Explicit Capture-Recapture

v4.4.1
GPL (>= 2)
Authors
Murray Efford
Initial release
2021-05-01

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