ForestHealth: Forest Health Data

Description

The data set consists of 16 variables with 1796 observations on forest health to identify potential factors influencing the health status of trees and therefore the vital status of the forest. In addition to covariates characterizing a tree and its stand, the exact locations of the trees are known. The interest is on detecting temporal and spatial trends while accounting for further covariate effects in a flexible manner.

Usage

data("ForestHealth")

Arguments

source

http://www.BayesX.org.

References

Kneib, T. & Fahrmeir, L. (2010): A Space-Time Study on Forest Health. In: Chandler, R. E. & Scott, M. (eds.): Statistical Methods for Trend Detection and Analysis in the Environmental Sciences, Wiley.

G"ottlein A, Pruscha H (1996). Der Einfuss von Bestandskenngr"ossen, Topographie, Standord und Witterung auf die Entwicklung des Kronenzustandes im Bereich des Forstamtes Rothenbuch. Forstwissens. Zent., 114, 146--162.

Examples

Run this code

## load zambia data and map
data("ForestHealth")
data("BeechBnd")

fm <- bayesx(defoliation ~  stand + fertilized + 
  humus + moisture + alkali + ph + soil + 
  sx(age) + sx(inclination) + sx(canopy) +
  sx(year) + sx(elevation),
  family = "cumlogit", method = "REML", data = ForestHealth)

summary(fm)
plot(fm, term = c("sx(age)", "sx(inclination)", 
  "sx(canopy)", "sx(year)", "sx(elevation)"))