FlexMix Interface to GAMs
This is a driver which allows fitting of mixtures of GAMs.
FLXMRmgcv(formula = . ~ ., family = c("gaussian", "binomial", "poisson"),
offset = NULL, control = NULL, optimizer = c("outer", "newton"),
in.out = NULL, eps = .Machine$double.eps, ...)formula |
A formula which is interpreted relative to the formula
specified in the call to |
family |
A character string naming a |
offset |
This can be used to specify an a priori known component to be included in the linear predictor during fitting. |
control |
A list of fit control parameters returned by
|
optimizer |
An array specifying the numerical optimization method
to use to optimize the smoothing parameter estimation criterion; for
more details see |
in.out |
Optional list for initializing outer iteration; for more
details see |
eps |
Observations with an a-posteriori probability smaller or
equal to |
... |
Additional arguments to be pased to the GAM fitter. |
Returns an object of class FLXMRmgcv.
Bettina Gruen
set.seed(2012)
x <- seq(0, 1, length.out = 100)
z <- sample(0:1, length(x), replace = TRUE)
y <- rnorm(length(x), ifelse(z, 5 * sin(x * 2 * pi), 10 * x - 5))
fitted_model <- flexmix(y ~ s(x), model = FLXMRmgcv(),
cluster = z + 1,
control = list(tolerance = 10^-3))
plot(y ~ x, col = clusters(fitted_model))
matplot(x, fitted(fitted_model), type = "l", add = TRUE)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.