plotxs {condvis} | R Documentation |
Visualise a section in data space
Description
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 |
model |
A fitted model object, or a list of such objects. |
model.colour |
Colours for fitted models. If |
model.lwd |
Line weight for fitted models. If |
model.lty |
Line style for fitted models. If |
model.name |
Character labels for models, for legend. |
yhat |
Fitted values for the observations in |
mar |
Margins for plot. |
col |
Colours for observed data. Should be of length |
weights |
Similarity weights for observed data. Should be of length
|
view3d |
Logical; if |
theta3d , phi3d |
Angles defining the viewing direction. |
xs.grid |
The grid of values defining the part of the section to visualise. Calculated if not provided. |
prednew |
The |
conf |
Logical; if |
probs |
Logical; if |
pch |
Plot symbols for observed data |
residuals |
Logical; if |
main |
Character title for plot, default is
|
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
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))