Number of segments in piecewise distribution



n = nsegments(pd) returns the number of segments in the piecewise distribution object pd.


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Generate a sample data set and fit a piecewise distribution with a Pareto tail to the data by using paretotails. Find the number of segments in the fitted distribution by using the object function nsegments.

Generate a sample data set containing 10% outliers in the right tail.

rng('default');  % For reproducibility
right_tail = exprnd(5,100,1);
center = randn(900,1);
x = [center;right_tail];

Create a paretotails object by fitting a piecewise distribution to x. Specify the boundaries of the tails using the lower and upper tail cumulative probabilities. Pass in 0 and 0.9 so that a fitted object does not contain a lower tail segment, and consists of the empirical distribution for the lower 90% of the data set and a generalized Pareto distribution (GPD) for the upper 10% of the data set.

pd = paretotails(x,0,0.9)
pd = 
Piecewise distribution with 2 segments
   -Inf < x < 1.73931  (0 < p < 0.9): interpolated empirical cdf
    1.73931 < x < Inf  (0.9 < p < 1): upper tail, GPD(0.643752,1.62246)

Return the number of segments in pd by using the nsegments function.

n = nsegments(pd)
n = 2

You can also get the number of segments by using the NumSegments property. Access the NumSegments property by using dot notation.

ans = 2

Input Arguments

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Piecewise distribution with Pareto tails, specified as a paretotails object.

Introduced in R2007a