A Tidy Framework for Changepoint Detection Analysis
Cumulative distribution of the exceedances of a time series
Convert changepoint sets to binary strings
Convert a date into a year
Convert, retrieve, or verify a model object
Convert, retrieve, or verify a segmenter object
Fit a model for mean and variance
Bayesian Maximum Descriptive Length
Initialize populations in genetic algorithms
Extract changepoints
Compare various models or algorithms for a given changepoint set
Use a changepoint set to break a time series into regions
Retrieve the degrees of freedom from a logLik object
Diagnose the fit of a segmented time series
Evaluate candidate changepoints sets
Generate a list of candidate changepoints using a genetic algorithm
Compute exceedances of a threshold for a time series
Obtain a descriptive filename for a tidycpt object
Regression-based model fitting
Fast implementation of meanshift model
Fit an NHPP model to one specific region
Fit a non-homogeneous Poisson process model to the exceedances of a ti...
Retrieve the optimal fitness (or objective function) value used by an ...
Class for model-fitting functions
Weibull distribution functions
Log-Likelihood functions for regions (Weibull)
Modified Bayesian Information Criterion
Maximum Descriptive Length
Base class for changepoint models
Retrieve the arguments that a model-fitting function used
Retrieve the name of the model that a segmenter or model used
Compute model variance
Retrieve parameters from a segmenter
Pad and unpad changepoint sets with boundary points
Diagnostic plots for seg_basket objects
Plot the intensity of an NHPP fit
Plot GA information
Objects exported from other packages
Default class for candidate changepoint sets
Base class for segmenters
Algoritmo genético de Bayesian MDL a un paso
Segment a time series using a genetic algorithm
Manually segment a time series
Segment a time series using the PELT algorithm
Segment a time series using a variety of algorithms
Convert changepoint sets to time indices
Format the coefficients from a linear model as a tibble
Simulate time series with known changepoint sets
tidychangepoint: A Tidy Framework for Changepoint Detection Analysis
Container class for tidycpt objects
Vectors implementation for logLik
Recover the function that created a model
Changepoint detection algorithms for R are widespread but have different interfaces and reporting conventions. This makes the comparative analysis of results difficult. We solve this problem by providing a tidy, unified interface for several different changepoint detection algorithms. We also provide consistent numerical and graphical reporting leveraging the 'broom' and 'ggplot2' packages.