plotMP {gamlss.mx} | R Documentation |
plotting mass points
Description
A utility function for plotting two dimension non-parametric distribution. The function uses the persp()
function.
Usage
plotMP(x, y, prob, theta = 20, phi = 20, expand = 0.5, col = "lightblue",
xlab = "intercept", ylab = "slope", ...)
Arguments
x |
a vector containg points in the x axis |
y |
a vector containg points in the y axis |
prob |
vector containing probabilities which should add up to one |
theta , phi , expand , col |
arguments to pass to the |
xlab |
the x label |
ylab |
the y label |
... |
additinal argument to be passed to |
Details
The function call
Value
A graph is produced.
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.
Stasinopoulos M.D., Kneib T, Klein N, Mayr A, Heller GZ. (2024) Generalized Additive Models for Location, Scale and Shape: A Distributional Regression Approach, with Applications. Cambridge University Press.
(see also https://www.gamlss.com/).
See Also
Examples
gamma_0 <- c( -4.4, -3,-2.2, -.5, 0.1, 1, 1.5, 2.2, 3.5, 4.1 )
gamma_1 <- c( 2.2, 1.2, 0.1, -1, -2.3, -4.6 , 5.1, -3.2, 0.1, -1.2)
prob <- c(0.1, .05, .12, 0.25, 0.08, 0.12, 0.10, 0.05, 0.10, 0.03 )
plotMP(gamma_0, gamma_1,prob)