data_xyplot: Plotting the response against the explanatory variables

In gamlss.ggplots: Plotting Generalised Additive Model for Location, Scale and Shape

Plotting the response against the explanatory variables

Description

The function data_xyplot() plots the response against all other variables in a given data set.

The function data_plot() plots all variables individually.

The function data_bucket() plots the bucket plot for all continuous variables.

The function data_zscores() calculates and plots the z-scores (obtained after fitting the SHASHo distribution) for all continuous variables.

The function y_zscores() calculates and plots the z-scores (obtained after fitting the SHASHo distribution) for a single variable.

Usage

data_xyplot(data, response, point.size = 0.5, nrow = NULL, ncol = NULL, 
          max.levels = 10, plots.per.page = 9, one.by.one = FALSE, 
          title, ...)
          
data_plot(data, value = 3, hist.col = "black", hist.fill = "white", 
           dens.fill = "#FF6666", nrow = NULL, ncol = NULL, 
           plot.hist = FALSE, plots.per.page = 9, one.by.one = FALSE, 
           title, ...) 
           
data_bucket(data, value = 3, max.levels = 20, 
           nrow = NULL, ncol = NULL, plots.per.page = 9, 
           one.by.one = FALSE, title, ...)  
           
y_zscores(x, family = SHASHo, plot = TRUE, hist = FALSE, ...)

data_zscores(data, plot.hist = TRUE, value = 3, family = SHASH,
          max.levels = 10, hist.col = "black", hist.fill = "white", 
          dens.fill = "#FF6666", nrow = NULL, ncol = NULL, 
          plots.per.page = 9, one.by.one = FALSE, title, ...)

Arguments

data	a data frame
x	a single variable
family	a gamlss distribution family (continuous)
response	the respose variable should be in the data
point.size	the size of points in scatter plots
nrow	the number of rows in the plot
ncol	the number of columns in the plot
plots.per.page	maximu plots per page
one.by.one	whether plotted individually
value	value to identify outliers if y_dots is used i.e. for upper tail an outliers is if it is greater than Q_3+value*IQ
hist.col	the colour of lines of the histogram, if plot.hist=TRUE
hist.fill	the colour of the histogram, if plot.hist=TRUE
dens.fill	the color of the density plot, if plot.hist=TRUE
plot.hist	whether to use y_dots() or y_hist() for the continuous variables
plot	whether to plot
hist	whether histiogram or dot plot
max.levels	excludes from plotting bucket plots for variables with less than max.levels, distinct values
title	title of the plot
...	other arguments

Details

The function data_xyplot() it takes a data frame and plot all the explanarory variables against the response.

The function data_plot() it takes a data frame and plot all variables against the response. The continuous are plotted using y_dots() or y_hist() while the factors and integer as bar plots.

Value

Plots of the data

Author(s)

Mikis Stasinopoulos

References

Rigby, R. A. and Stasinopoulos D. M. (2005). Generalized additive models for location, scale and shape,(with discussion), Appl. Statist., 54, part 3, pp 507-554.

Rigby, R. A., Stasinopoulos, D. M., Heller, G. Z., and De Bastiani, F. (2019) Distributions for modeling location, scale, and shape: Using GAMLSS in R, Chapman and Hall/CRC. An older version can be found in https://www.gamlss.com/.

Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R. Journal of Statistical Software, Vol. 23, Issue 7, Dec 2007, https://www.jstatsoft.org/v23/i07/.

Stasinopoulos D. M., Rigby R.A., Heller G., Voudouris V., and De Bastiani F., (2017) Flexible Regression and Smoothing: Using GAMLSS in R, Chapman and Hall/CRC.

(see also https://www.gamlss.com/).

See Also

data_names

Examples

da <- rent99[,-2]
data_xyplot(da, rent)
data_plot(da)
y_zscores(da$rent)

gamlss.ggplots documentation built on Sept. 3, 2023, 5:08 p.m.