# Default plotting for wavelet-domain scalar-on-function regression

### Description

Plots the coefficient function/image estimates produced by `wcr`

and `wnet`

.

### Usage

1 2 3 4 5 6 | ```
## S3 method for class 'wcr'
plot(x, xlabel = "", ylabel = "Coefficient function", which.dim = 1, slices = NULL,
set.mfrow = TRUE, image.axes = FALSE, ...)
## S3 method for class 'wnet'
plot(x, xlabel = "", ylabel = "Coefficient function", which.dim = 1, slices = NULL,
set.mfrow = TRUE, image.axes = FALSE, ...)
``` |

### Arguments

`x` |
an object of class |

`xlabel, ylabel` |
for 1D functional predictors, x- and y-axis labels. |

`which.dim, slices` |
for 3D image predictors, the dimension (1, 2 or 3) and slices to use for plotting; see Details. |

`set.mfrow` |
logical value: for 3D predictors, if |

`image.axes` |
for 2D and 3D predictors, the |

`...` |
additional parameters passed to |

### Details

As an example of how `which.dim`

and `slices`

are used, suppose we set `which.dim=2`

and `slices=7:9`

. Then three 2D slices of the coefficient image estimate `x$fhat`

are displayed: `x$fhat[ , 7, ]`

, `x$fhat[ , 8, ]`

, and `x$fhat[ , 9, ]`

.

### Author(s)

Lan Huo lan.huo@nyumc.org

### See Also

`wcr`

and `wnet`

; the latter includes examples.

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