This package implements the species modelling algorithm called WhyWhere documented in the article “Improving ecological niche models by data mining large environmental datasets for surrogate models” by David R.B. Stockwell in Ecological Modelling Volume 192, Issues 1–2, 15 February 2006, Pages 188–196. (PDF).
Download the package WhyWhere_0.1.tar
This package performs operations known as “homogenization” on time series data that is subject to various non-natural anomalies such as instrument baseline changes and spikes.
Preliminary testing indicates that it has a considerably higher sensitivity to small baseline shifts than a Chow test. Below is a scatterplot of the size of a single shift on a series of length 10. These series and the shift both had a standard deviation of one, which is similar to an annual temperature series.
The Chow test – red dots I(0) – does not reliabily detect a change in level until around 1 degree C. However the new method – blue dots I(1) – reliably detects changes in level down to around 0.25 degrees C.
Download the R package for testing here: Anomaly_0.1.tar