print.secr {secr} | R Documentation

## 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, and date and time fitting started
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

`AIC.secr`, `secr.fit`

### 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)

[Package secr version 3.2.1 Index]