Plot a fitted circular mixture

Clustered views of a fitted mixture. The flat view colours the observations by their MAP cluster, with – for a regression cell – each component's fitted location curve over the single covariate, or – for a density cell (theta ~ 1) – the per-cluster spread of the response with each component's fitted mean direction. The geometry view draws those per-component curves on the leg's natural 3D surface (cylinder / torus / can).

Usage

# S3 method for class 'circ_mix'
plot(x, view = c("flat", "geometry", "both"), n = 200, se = TRUE, ...)

Arguments

x

A fitted circ_mix object.

view

Which view to draw. "flat" (default) draws the flat panel. "geometry" draws every component's fitted location curve on the leg's natural surface – the cylinder (c~l), torus (c~c) or can (l~c), sharing plot.circ_gam's surface canvas; "both" places the two side by side. A joint (product) component has only the flat torus-square projection, so it draws that whatever the view.

n

Number of grid points for each component's fitted curve.

se

If TRUE, band each component's fitted curve where the view supports it: \(\pm\) the component law's circular standard deviation (its predictive angular spread) for a circular response, a pointwise 2-SE interval for a linear response.

...

Further graphical arguments (currently unused).

Value

x, invisibly. Called for the plot it draws.

See also

circ_mix, plot.circ_gam

Examples

library(mgcv)
set.seed(1); n <- 400
z  <- sample.int(2L, n, replace = TRUE)
x  <- runif(n, -1, 1)
mu <- 2 * atan(c(1, -1)[z] + c(2, -2)[z] * x)
y  <- vmlss()$rd(cbind(mu, rep(6, n)), rep(1, n), 1)
# \donttest{
m  <- circ_mix(y ~ x, data = data.frame(y, x), family = vmlss(), K = 2)
plot(m)
# }