This is a supplementary dataset (used as a test set for the pine
dataset) that was extracted from a 1973 study on pine_sup processionary
caterpillars. It assesses the influence of some forest settlement
characteristics on the development of caterpillar colonies. The response
variable is the logarithmic transform of the average number of nests of
caterpillars per tree in an area of 500 square meters (x11). There
are k=10 potentially explanatory variables defined on n=22 areas.
A data frame with 22 observations on the following 11 variables.
altitude (in meters)
slope (en degrees)
number of pine_sups in the area
height (in meters) of the tree sampled at the center of the area
diameter (in meters) of the tree sampled at the center of the area
index of the settlement density
orientation of the area (from 1 if southbound to 2 otherwise)
height (in meters) of the dominant tree
number of vegetation strata
mix settlement index (from 1 if not mixed to 2 if mixed)
logarithmic transform of the average number of nests of caterpillars per tree
These caterpillars got their names from their habit of moving over the
ground in incredibly long head-to-tail processions when leaving their nest
to create a new colony.
The pine_sup dataset can be used as a test set to assess model
prediction error of a model trained on the pine dataset.
J.-M. Marin, C. Robert. (2007). Bayesian Core: A Practical Approach to Computational Bayesian Statistics. Springer, New-York, pages 48-49.