Rdistance (version 4.0.5)

summary.dfunc: Summarize a distance function object

Description

A summary method for distance functions. Distance functions are produced by dfuncEstim (class dfunc).

Usage

# S3 method for dfunc
summary(object, criterion = "AICc", ...)

Value

The input distance function object (object), invisibly, with the following additional components:

• convMessage: The convergence message. If the distance function is smoothed, the convergence message is NULL.

• effDistance: The ESW or EDR.

• pDetect: Probability of detection in the strip.

• AIC: AICc, AIC, or BIC of the fit, whichever was requested.

• coefficients: If the distance function has coefficients, this is the coefficient matrix with standard errors, Wald Z values, and p values. If the distance function is smoothed, it has no coefficients and this component is NULL.

Arguments

object

An Rdistance model frame or fitted distance function, normally produced by a call to dfuncEstim.

criterion

A string specifying the model fit criterion to print. Must be one of "AICc" (the default), "AIC", or "BIC". See AIC.dfunc for formulas.

...

Included for compatibility with other print methods. Ignored here.

Details

This function prints the following quantities:

• Call : The original function call.

• Coefficients : A matrix of estimated coefficients, their standard errors, and Wald Z tests.

• Strip : The left (w.lo) and right (w.hi) truncation values.

• Effective strip width or detection radius : ESW or EDR as computed by effectiveDistance.

• Probability of Detection : Probability of detecting a single target in the strip.

• Scaling : The horizontal and vertical coordinates used to scale the distance function. Usually, the horizontal coordinate is 0 and the vertical coordinate is 1 (i.e., g(0) = 1).

• Log likelihood : Value of the maximized log likelihood.

• Criterion : Value of the specified fit criterion (AIC, AICc, or BIC).

The number of digits used in the printout is controlled by options()$digits.

See Also

dfuncEstim, plot.dfunc, print.abund, print.abund

Examples

# Load example sparrow data (line transect survey type)
data(sparrowDf)

# Fit half-normal detection function
dfunc <- sparrowDf |> dfuncEstim(formula=dist~1)

# Print results
summary(dfunc)
summary(dfunc, criterion="BIC")