R: FlexMix Interface to GAMs

FLXMRmgcv {flexmix} | R Documentation

## FlexMix Interface to GAMs

### Description

This is a driver which allows fitting of mixtures of GAMs.

### Usage

    FLXMRmgcv(formula = . ~ ., family = c("gaussian", "binomial", "poisson"),
              offset = NULL, control = NULL, optimizer = c("outer", "newton"),
              in.out = NULL, eps = .Machine$double.eps, ...)

### Arguments

`formula` | A formula which is interpreted relative to the formula specified in the call to `flexmix` using `update.formula`. Default is to use the original `flexmix` model formula.
`family` | A character string naming a `glm` family function.
`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 `gam.control`.
`optimizer` | An array specifying the numerical optimization method to use to optimize the smoothing parameter estimation criterion; for more details see `gam`.
`in.out` | Optional list for initializing outer iteration; for more details see `gam`.
`eps` | Observations with an a-posteriori probability smaller or equal to `eps` are omitted in the M-step.
`...` | Additional arguments to be pased to the GAM fitter.

### Value

Returns an object of class `FLXMRmgcv`.

### Author(s)

Bettina Gruen

### See Also

`FLXMRglm`

### Examples

    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)

[Package flexmix version 2.3-14 Index]