summary.quax: Summarizing quantile regression fits of potential...

In quaxnat: Estimation of Natural Regeneration Potential

Summarizing quantile regression fits of potential regeneration densities

Description

This function is the summary method for class quax objects as returned by quax.

Usage

## S3 method for class 'quax'
summary(object, ...)

Arguments

object	The function returned by quax.
...	not in use here

Details

The value component of the result can be used to compare the quality of the fit of different dispersal kernels for the same quantile to the same data.

Value

A list with the following components:

coefficients

The parameters of the estimated dispersal kernel.

value

The attained value of the objective function that is minimised in the quantile regression.

Examples

## Prepare artificial data:
set.seed(0)
r <- rgamma(200, shape=2, scale=150)
simulated.data <- data.frame(distance = r, density =
  rpois(length(r), k_lognormal(r, par=c(6,0), N=1000000, d=2)))
plot(density ~ distance, simulated.data)

## Fit a log-normal and a power-law dispersal kernel to the data:
f1 <- quax(density ~ distance, simulated.data,
  tau = 0.9, fun = k_lognormal)
f2 <- quax(density ~ distance, simulated.data,
  tau = 0.9, fun = k_power)

## Compare both fits:
summary(f1)
summary(f2)

quaxnat documentation built on Oct. 28, 2024, 5:08 p.m.