pcurve.data: Example data for pcurve

In s-u/pcurve: Principal curve analysis

Description

Example data sets for pcurve package.

Usage

  data(sim4var)
  data(sim10var)
  data(fish)
  data(soilspec)

Details

sim4var.txt

Simulated data. Comprises 4 response variables (Taxa1 - Taxa4) and the generating locations (Location). Number of cases = 100. This example was worked by De'ath (1999). The response curves are Gaussian and noise is Poisson. Most starting configurations are adequate, square root transformation helps.

sim10var.txt

Simulated data. Comprises 10 response variables (Taxa1 - Taxa10) and the generating locations (Location). Number of cases = 100. The response curves are Gaussian and noise is Poisson. The beta-diversity is high and recovering the generating locations is difficult. A more difficult exercise. Transformation is a must (square-root is ok). Many starting configurations fail. CA or MDS-BC succeed with appropriate smoothness.

fish.txt

Comprises counts on 10 families of reef fish (n = 33) and a factor variable IMO denoting the position of the sites across the reef. Log-transformation is effective and a final cross-validation helps improve the fit. The locations vary systematically with cross shelf position (IMO).

soilspec.txt

Comprises data on 8 species of plants and 3 soil characteristics and their interactions. Source Gittins (1985), where a relatively complex canonical analysis was used to model the data. This example was worked by De'ath (1999).

Author(s)

R port by Chris Walsh [e-mail] from S+ library by Glenn De'ath [e-mail].

References

De'ath, G. 1999 Principal Curves: a new technique for indirect and direct gradient analysis. Ecology 80, 2237–2253.

Gittins, R. 1985 Canonical Analysis. A review with applications in ecology. Berlin: Springer-Verlag.

s-u/pcurve documentation built on May 28, 2019, 10:48 a.m.