R: Unidimensional and Multidimensional Methods for Recurrence Quantification Analysis

# Unidimensional and Multidimensional Methods for Recurrence Quantification Analysis

## Documentation for package ‘crqa’ version 2.1.0

- DESCRIPTION file
- User guides, package vignettes and other documentation

## Help Pages

crqa-package | Unidimensional and Multidimensional Methods for Recurrence Quantification Analysis
aRQA | Approximative 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
rosslerattractor | Simulate a Roessler attractor
simts | Simulate dichotomous binary time-series
spdiags | Extract diagonal matrices
text | Categorical sequence of words
theiler_exclusion | Number of cells excluded by a Theiler window
wincrqa | Windowed Recurrence Measures
windowdrp | Windowed Recurrence Profile