Unidimensional and Multidimensional Methods for Recurrence Quantification Analysis


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Documentation for package ‘crqa’ version 2.0.6

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crqa-package Unidimensional and Multidimensional Methods for Recurrence Quantification Analysis
crqa Auto, cross and multidimensional recurrence measures of one, two or multiple time-series, time-delayed and embedded in higher dimensional space
drpfromts Diagonal recurrence profile
eyemovement Eye-movement categorical time-series
Figure_1 Eye-movement categorical time-series
Figure_2 A unidimensional sinusoidal time series
Figure_3 Simulated time series of the three dimensions from the Lorenz system
Figure_6 Figure_6
handmovement Continuous series of hand movements
lorenzattractor Simulate the Lorenz Attractor
mdDelay Find optimal delay from a multi-dimensional dataset.
mdFnn Find optimal embedding dimension of a multi-dimensional dataset.
optimizeParam Estimate optimal delay, embedding dimension and radius for continuous time-series data
piecewiseRQA Compute recurrence plots for long time-series data series using a block (piece-wise) method.
plot_rp Plot a recurrence matrix
simts Simulate dichotomous binary time-series
spdiags Extract diagonal matrices
text Categorical sequence of words
wincrqa Windowed Recurrence Measures
windowdrp Windowed Recurrence Profile