Model responses according to a Gaussian mixture.

Objects can be created by calls of the form `new("GaussianMixtureResponse", ...)`

.

`weights`

:A

`"list"`

, with for each repetition in nTimes, a T*K matrix of mixture weights (T=total number of trials, k = number of mixture components).`means`

:A

`"list"`

, with for each repetition in nTimes, a matrix of mixture means. When component means vary over trials, this should be a T*K matrix (T=total number of trials, k = number of mixture components), else a 1*k matrix.`sds`

:A

`"list"`

, with for each repetition in nTimes, the standard deviation of the mixture components. Currently, only components with identical means are supported, and the values in this slot are set by a single "sd" parameter (see "parameters" slot).`x`

:A

`"matrix"`

, containing values of the response options.`y`

:Object of class

`"matrix"`

, containing dummy coded response variable.`parStruct`

:Object of class

`"ParStruct"`

, specifying parameters and (optional) constraints.`nTimes`

:Object of class

`"NTimes"`

.

Class `"ResponseModel"`

, directly.
Class `"McplBaseModel"`

, by class "ResponseModel", distance 2.

- fit
`signature(object = "GaussianMixtureResponse")`

: ...- logLik
`signature(object = "GaussianMixtureResponse")`

: ...- predict
`signature(object = "GaussianMixtureResponse")`

: ...

Maarten Speekenbrink

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

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