Detecting Breakpoints and Estimating Segments in Trend (DBEST)
An algorithm for analysing vegetation time series with two main application domains - generalising vegetation trends and characterizing vegetation trend changes. The algorithm simplifies the trend into linear segments using one of three parameters: a generalisation threshold parameter, the largest changes, or a threshold for the magnitude of changes. The outputs are the simplified trend, the change type (abrupt or non-abrupt), and the time and magnitude of the change.

Detecting Breakpoints and Estimating Segments in Trend
A program for analyzing vegetation time series, with two algorithms: 1) change detection algorithm that detects trend changes, determines their type (abrupt or non-abrupt), and estimates their timing, magnitude, number, and direction; 2) generalization algorithm that simplifies the temporal trend into main features. The user can set the number of major breakpoints or magnitude of greatest changes of interest for detection, and can control the generalization process by setting an additional parameter of generalization-percentage.

DBF test of no difference between groups
Distance-based test of no difference between groups.

methods of distance-based gene set functional enrichment
analysis
This package provides methods and examples to support a
method of disease-based Gene Set Functional Enrichment Analysis
(GSFEA).
avelinkdis.R centdis.R distable.R randdis.R valuep.R
functionall.R

methods of distance-based gene set functional enrichment
analysis.
This package provides methods and examples to support a
method of Gene Set Functional Enrichment Analysis (GSFEA).
DBGSA is a novel distance-based gene set enrichment analysis
method. We consider that, the distance between 2 groups with
different phenotype by focusing on the gene expression should
be larger, if a certain gene functional set was significantly
associated with a particular phenotype.

This package provides methods and examples to support a
method of Gene Set Analysis (GSA).  DBGSA is a novel
distance-based gene set enrichment analysis method. We consider
that, the distance between 2 groups with different phenotype by
focusing on the gene expression should be larger, if a certain
gene functional set was significantly associated with a
particular phenotype.