plot.lpcde {lpcde}

Plot method for local polynomial density conditional estimation

Description

The plot method for local polynomial density objects. A standard ggplot2 object is returned, hence can be used for further customization.

Usage

## S3 method for class 'lpcde'
plot(
  ...,
  alpha = NULL,
  type = NULL,
  lty = NULL,
  lwd = NULL,
  lcol = NULL,
  pty = NULL,
  pwd = NULL,
  pcol = NULL,
  y_grid = NULL,
  CItype = NULL,
  CIuniform = FALSE,
  CIsimul = 2000,
  CIshade = NULL,
  CIcol = NULL,
  title = NULL,
  xlabel = NULL,
  ylabel = NULL,
  legendTitle = NULL,
  legendGroups = NULL,
  rbc = FALSE
)

Arguments

...

Class "lpcde" object, obtained from calling lpcde.

alpha

Numeric scalar between 0 and 1, specifies the significance level for plotting confidence intervals/bands.

type

String, one of "line" (default), "points" and "both", specifies how the point estimates are plotted. If more than one is provided, they will be applied to each data series accordingly.

lty

Line type for point estimates, only effective if type is "line" or "both". 1 for solid line, 2 for dashed line, 3 for dotted line. For other options, see the instructions for ggplot2 . If more than one is provided, they will be applied to each data series accordingly.

lwd

Line width for point estimates, only effective if type is "line" or "both". Should be strictly positive. For other options, see the instructions for ggplot2 . If more than one is provided, they will be applied to each data series accordingly.

lcol

Line color for point estimates, only effective if type is "line" or "both". 1 for black, 2 for red, 3 for green, 4 for blue. For other options, see the instructions for ggplot2 . If more than one is provided, they will be applied to each data series accordingly.

pty

Scatter plot type for point estimates, only effective if type is "points" or "both". For options, see the instructions for ggplot2 . If more than one is provided, they will be applied to each data series accordingly.

pwd

Scatter plot size for point estimates, only effective if type is "points" or "both". Should be strictly positive. If more than one is provided, they will be applied to each data series accordingly.

pcol

Scatter plot color for point estimates, only effective if type is "points" or "both". 1 for black, 2 for red, 3 for green, 4 for blue. For other options, see the instructions for ggplot2 . If more than one is provided, they will be applied to each data series accordingly.

y_grid

Numeric vector, specifies a subset of grid points to plot point estimates. This option is effective only if type is "points" or "both"; or if CItype is "ebar" or "all".

CItype

String, one of "region" (shaded region, default), "line" (dashed lines), "ebar" (error bars), "all" (all of the previous) or "none" (no confidence region), how the confidence region should be plotted. If more than one is provided, they will be applied to each data series accordingly.

CIuniform

TRUE or FALSE (default), plotting either pointwise confidence intervals (FALSE) or uniform confidence bands (TRUE).

CIsimul

Positive integer, specifies the number of simulations used to construct critical values (default is 2000). This option is ignored if CIuniform=FALSE.

CIshade

Numeric, specifies the opaqueness of the confidence region, should be between 0 (transparent) and

1. Default is 0.2. If more than one is provided, they will be applied to each data series accordingly.

CIcol

Color of the confidence region. 1 for black, 2 for red, 3 for green, 4 for blue. For other options, see the instructions for ggplot2 . If more than one is provided, they will be applied to each data series accordingly.

title, xlabel, ylabel

Strings, specifies the title of the plot and labels for the x- and y-axis.

legendTitle

String, specifies the legend title.

legendGroups

String vector, specifies the group names used in legend.

rbc

TRUE or FALSE (default), plotting confidence intervals and bands with standard estimates (FALSE) or RBC estimates (TRUE).

Value

Figure

A standard ggplot2 object is returned, hence can be used for further customization.

Author(s)

Matias D. Cattaneo, Princeton University. [e-mail].

Rajita Chandak (maintainer), Princeton University. [e-mail]

Michael Jansson, University of California Berkeley. [e-mail].

Xinwei Ma, University of California San Diego. [e-mail].

See Also

lpcde for local polynomial density estimation. Supported methods: coef.lpcde, confint.lpcde, plot.lpcde, print.lpcde, summary.lpcde, vcov.lpcde