The Poincare plot is a graphical representation of the dependance
between successive RR intervals obtained by plotting the *RR_(j+tau)*
as a function of *RR_j*. This dependance is often quantified by fitting an
ellipse to the plot. In this way, two parameters are obtained:
*SD_1* and *SD_2*.
*SD_1* characterizes short-term variability
whereas that *SD_2* characterizes long-term variability.

1 2 3 4 5 | ```
PoincarePlot(HRVData,
indexNonLinearAnalysis = length(HRVData$NonLinearAnalysis), timeLag = 1,
confidenceEstimation = FALSE, confidence = 0.95, doPlot = FALSE,
main = "Poincare plot", xlab = "RR[n]", ylab = paste0("RR[n+", timeLag,
"]"), pch = 1, cex = 0.3, type = "p", xlim = NULL, ylim = NULL, ...)
``` |

`HRVData` |
Data structure that stores the beats register and information related to it |

`indexNonLinearAnalysis` |
Reference to the data structure that will contain the nonlinear analysis |

`timeLag` |
Integer denoting the number of time steps that will be use to construct the
dependance relation: |

`confidenceEstimation` |
Logical value. If TRUE, the covariance matrix is
used for fitting the ellipse and computing the |

`confidence` |
The confidence used for plotting the confidence ellipse. |

`doPlot` |
Logical value. If TRUE (default), the PoincarePlot is shown. |

`main` |
An overall title for the Poincare plot. |

`xlab` |
A title for the x axis. |

`ylab` |
A title for the y axis. |

`pch` |
Plotting character (symbol to use). |

`cex` |
Character (or symbol) expansion. |

`type` |
What type of plot should be drawn. See |

`xlim` |
x coordinates range. If not specified, a proper x range is selected. |

`ylim` |
y coordinates range. If not specified, a proper y range is selected. |

`...` |
Additional parameters for the Poincare plot figure. |

In the HRV literature, when *timeLag = 1*, the *SD_1* and *SD_2*
parameters are computed using time domain measures. This is the default approach in this
function if *timeLag=1*. This function also allows the user to fit a ellipse
by computing the covariance matrix of
(*RR_(j)*,*RR_(j+tau)*)
(by setting *confidenceEstimation = TRUE*). In most cases, both approaches
yield similar results.

A *HRVData* structure containing a *PoincarePlot* field storing
the *SD_1* and *SD_2* parameters. The *PoincarePlot* field is
stored under the *NonLinearAnalysis* list.

1 2 3 4 5 6 7 8 | ```
## Not run:
data(HRVProcessedData)
# rename for convenience
hd = HRVProcessedData
hd = CreateNonLinearAnalysis(hd)
hd = PoincarePlot(hd, doPlot = T)
## End(Not run)
``` |

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