strucchange algorithm

Knowledge graph centered on strucchange algorithm with 17 nodes and 44 connections. Top connected: Crested Butte, Engelmann Spruce, Salix lucida subsp. lasiandra, Abies lasiocarpa, Water balance equation.

Method synopsis

Statistical method using the strucchange package in R to detect structural changes in meteorological time series by evaluating F-statistics and identifying optimal breakpoints using dynamic programming. Applied to identify temporal segments in temperature and precipitation data.

Synthesized from method descriptions across 1 paper using this protocol.

Procedure from a recent peer-reviewed implementation

Steps below were extracted from the most recent peer-reviewed implementation of this protocol in the corpus — Statistical framework to assess long-term spatio-temporal climate changes: East River mountainous watershed case study (2022), Stochastic environmental research and risk assessment. Implementations in other papers (listed below) may differ.

1. Detect temporal structural breakpoints
   Apply the strucchange package in R to analyze time series for trend structural changes using breakpoints or shifts of time series based on evaluation of the F-statistic by means of assessing deviations in the classical linear regression model. The algorithm computes the optimal breakpoints given the number of breaks based on dynamic programming approach of Bellman's principle of optimality. The function uses minimal number of observations from 150 to 200 days in each time series segment with residual sum of squares (RSS) and Bayesian Information Criterion (BIC) function drop sharply up to 2 breakpoints.
   Quantities: Applied to time series from all 17 locations with 150-200 days minimum per segment, maximum 2 breakpointsDuration: Applied to yearly averaged temperature and precipitation time seriesConditions: Standard statistical analysis conditions
   Equipment: R strucchange package, F-statistic evaluation, BIC function, RSS calculation

Typical Equipment

• R strucchange package
• F-statistic evaluation
• BIC function
• RSS calculation

Output Measurements

• temporal breakpoints
• confidence intervals
• time series segments

Papers Using This Protocol (1)

Species Studied With This Protocol

Places Where Used