Description Objects from the Class Slots Methods Author(s) See Also Examples
A class for online changepoint objects, specifically change in regression.
Objects can be created by calls of the form new("ocpt", ...).
new("ocpt", ...):creates a new object with class ocpt
sumstat:Object of class "numeric", the summary statistic matrix for the data
cpttype:Object of class "character", the type of online changepoint that was identified
method:Object of class "character", the method that was used to search for online changepoints, default change in regression
test.stat:Object of class "character", the test statistic used to analyse the data
pen.type:Object of class "character", the penalty type specified in the analysis
pen.value:Object of class "numeric", the value of the penalty used in the analysis
minseglen:Object of class "numeric", the minimum segment length (no. of observations between online changepoints) used in the analysis.
cpts:Object of class "numeric", vector of online changepoints identified
ncpts.max:Object of class "numeric", maximum number of online changepoint that can be identified
param.est:Object of class "list", list where each element is a vector of parameter estimates, if requested
date:Object of class "character", date and time the online changepoint analysis was run
version:Object of class "character", version number of the package used when the analysis was run.
lastchangelike:Object of class "numeric", vector of lenght n containing the likelihood of the optimal segmentation up to each timepoint.
lastchangecpts:Object of class "numeric", vector of length n containing the last changepoint prior to each timepoint.
nchecklist:Object of class "numeric", stores the current number of changepoints detected.
checklist:Object of class "numeric", vector of locations of the potential last changepoint for next iteration (to be updated), max length=(ndone+nupdate).
ndone:Object of class "numeric", length of the time series when analysis begins.
nupdate:Object of class "numeric", length of the time series to be analysed in this update.
cost_func:Object of class "character", the cost function used in PELT.online calculations.
shape:Object of class "numeric", only used when cost_func is the gamma likelihood. Otherwise 1.
signature(object = "ocpt.reg"): retrieves cpts slot
signature(object = "ocpt.reg"): retrieves cpttype slot
signature(object = "ocpt.reg"): retrieves sumstat slot
signature(object = "ocpt.reg"): retrieves test.stat slot
signature(object = "ocpt.reg"): retrieves ncpts.max slot
signature(object = "ocpt.reg"): retrieves method slot
signature(object = "ocpt"): retrieves minseglen slot
signature(object = "ocpt.reg"): retrieves param.est slot
signature(object = "ocpt.reg"): retrieves pen.type slot
signature(object = "ocpt.reg"): retrieves pen.value slot
signature(object = "ocpt.reg"): replaces cpts slot
signature(object = "ocpt.reg"): replaces cpttype slot
signature(object = "ocpt.reg"): replaces sumstat slot
signature(object = "ocpt.reg"): replaces test.stat slot
signature(object = "ocpt.reg"): replaces ncpts.max slot
signature(object = "ocpt.reg"): replaces method slot
signature(object = "ocpt.reg"): replaces param.est slot
signature(object = "ocpt.reg"): replaces pen.type slot
signature(object = "ocpt.reg"): replaces pen.value slot
signature(object = "ocpt.reg"): prints details of the cpt object including summary
signature(object = "ocpt.reg"): prints a summary of the ocpt object
signature(object = "ocpt.reg"): calculates the parameter estimates for the ocpt object
Andrew Connell Rebecca Killick
plot-methods,cpts-methods,ocpt
1 2 3 4 5 |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.