Visualize the imputed values in a time series.

1 2 3 4 5 6 7 | ```
plotNA.imputations(x.withNA, x.withImputations, x.withTruth = NULL,
legend = TRUE, main = "Visualization Imputed Values", xlab = "Time",
ylab = "Value", colWithTruth = "green3", colLines = "black",
colWithImputations = "indianred2", colWithNA = "steelblue2",
ylim = c(min(c(x.withImputations, x.withTruth), na.rm = TRUE),
max(c(x.withImputations, x.withTruth), na.rm = TRUE)), pch = 20,
cex = 0.8, ...)
``` |

`x.withNA` |
Numeric Vector or Time Series ( |

`x.withImputations` |
Numeric Vector or Time Series ( |

`x.withTruth` |
Numeric Vector or Time Series ( |

`legend` |
If TRUE a legend is shown at the bottom of the plot. A custom legend can be obtained by
setting this parameter to FALSE and using |

`main` |
Main title for the plot |

`xlab` |
Label for x axis of the plot |

`ylab` |
Label for y axis of plot |

`colWithTruth` |
Defines the color of the real values (truth) for the NA values. |

`colLines` |
Defines the color of the lines connecting non-NA observations. |

`colWithImputations` |
Defines the color for the imputed values. |

`colWithNA` |
Defines the color of the non-NA observations. |

`ylim` |
the y limits of the plot |

`pch` |
Either an integer specifying a symbol or a single character to be used as the default in plotting points. |

`cex` |
A numerical value giving the amount by which plotting text and symbols should be magnified relative to the default. |

`...` |
Additional graphical parameters that can be passed through to plot |

This plot can be used, to visualize the imputed values for a time series. Therefore, the imputed values (filled NA gaps) are shown in a different color than the other values. If the real values (truth) behind the NA gaps are known these are also added in a different color.

Steffen Moritz

`plotNA.distribution`

,`plotNA.distributionBar`

,
`plotNA.gapsize`

1 2 3 4 5 6 7 8 | ```
#Example 1: Visualize the values that were imputed by na.mean in the time series
impMean.Airgap <- na.mean(tsAirgap)
plotNA.imputations(tsAirgap, impMean.Airgap)
#Example 2: Visualize the values that were imputed by na.locf and the true values in the time series
impLOCF.Airgap <- na.locf(tsAirgap)
plotNA.imputations(tsAirgap, impLOCF.Airgap, tsAirgapComplete)
``` |

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