# plotxs

##### Visualise a section in data space

Visualise a section in data space, showing fitted models where
they intersect the section, and nearby observations. The `weights`

for
observations can be calculated with `similarityweight`

. This
function is mainly for use in `ceplot`

and
`condtour`

.

##### Usage

```
plotxs(xs, y, xc.cond, model, model.colour = NULL, model.lwd = NULL,
model.lty = NULL, model.name = NULL, yhat = NULL, mar = NULL,
col = "black", weights = NULL, view3d = FALSE, theta3d = 45,
phi3d = 20, xs.grid = NULL, prednew = NULL, conf = FALSE,
probs = FALSE, pch = 1, residuals = FALSE, main = NULL, xlim = NULL,
ylim = NULL)
```

##### Arguments

- xs
A dataframe with one or two columns.

- y
A dataframe with one column.

- xc.cond
A dataframe with a single row, with all columns required for passing to

`predict`

methods of models in`model`

.- model
A fitted model object, or a list of such objects.

- model.colour
Colours for fitted models. If

`model`

is a list, this should be of same length as`model`

.- model.lwd
Line weight for fitted models. If

`model`

is a list, this should be of same length as`model`

.- model.lty
Line style for fitted models. If

`model`

is a list, this should be of same length as`model`

.- model.name
Character labels for models, for legend.

- yhat
Fitted values for the observations in

`y`

. Calculated if needed and not provided. Only used if showing residuals, or`xs`

has two columns.- mar
Margins for plot.

- col
Colours for observed data. Should be of length

`nrow(xs)`

.- weights
Similarity weights for observed data. Should be of length

`nrow(xs)`

. Usually calculated with`similarityweight`

.- view3d
Logical; if

`TRUE`

plots a three-dimensional regression surface if possible.- theta3d, phi3d
Angles defining the viewing direction.

`theta3d`

gives the azimuthal direction and`phi3d`

the colatitude. See`persp`

.- xs.grid
The grid of values defining the part of the section to visualise. Calculated if not provided.

- prednew
The

`y`

values where the models in`model`

intersect the section. Useful when providing`theta3d`

,`phi3d`

, or`weights`

, where the predict methods have been called elsewhere.- conf
Logical; if

`TRUE`

plots confidence bounds (or equivalent) for models which provide this.- probs
Logical; if

`TRUE`

, shows predicted class probabilities instead of just predicted classes. Only available if`xs`

contains two numeric predictors and the model's predict method provides this.- pch
Plot symbols for observed data

- residuals
Logical; if

`TRUE`

, plots a residual versus predictor plot instead of the usual scale of raw response.- main
Character title for plot, default is

`"Conditional expectation"`

.- xlim
Graphical parameter passed to plotting functions.

- ylim
Graphical parameter passed to plotting functions.

##### Value

A list containing relevant information for updating the plot.

##### References

O'Connell M, Hurley CB and Domijan K (2017). ``Conditional
Visualization for Statistical Models: An Introduction to the
**condvis** Package in R.''*Journal of Statistical Software*,
**81**(5), pp. 1-20. <URL:http://dx.doi.org/10.18637/jss.v081.i05>.

##### See Also

##### Examples

```
# NOT RUN {
data(mtcars)
model <- lm(mpg ~ ., data = mtcars)
plotxs(xs = mtcars[, "wt", drop = FALSE], y = mtcars[, "mpg", drop = FALSE],
xc.cond = mtcars[1, ], model = list(model))
# }
```

*Documentation reproduced from package condvis, version 0.5-1, License: GPL (>= 2)*