R: Carry out mulitple independent smoothing-splines...

sme.list {sme} | R Documentation

## Carry out mulitple independent smoothing-splines mixed-effects model fits simultaneously

### Description

Carry out multiple independent smoothing-splines mixed-effects model fits simultaneously

### Usage

    ## S3 method for class 'list'
    sme(object,tme,ind,verbose=F,lambda.mu=NULL,lambda.v=NULL,maxIter=500,
    knots=NULL,zeroIntercept=F,deltaEM=1e-3,deltaNM=1e-3,criteria="AICc",
    numberOfThreads=-1,...)

### Arguments

`object` | a list of vectors of observations
`tme` | a list of vectors of time points corresponding to the observations in `object`
`ind` | a list of factors (or vectors that can be coerced to factors) of subject identifiers corresponding to the observations in `object`
`verbose` | if `TRUE`, debug information will be output while fitting the model(s)
`lambda.mu` | either a single smoothing parameter to be used for the fixed-effect function for all fits, or a vector of smoothing parameters, one for each fit, or `NULL` if Nelder-Mead search should be used to find the optimal values for this and `lambda.v` for all fits
`lambda.v` | either a single smoothing parameter to be used for the random-effects functions for all fits, or a vector of smoothing parameters, one for each fit, or `NULL` if Nelder-Mead search should be used to find the optimal values for this and `lambda.v` for all fits
`maxIter` | maximum number of iterations to be performed for the EM algorithm
`knots` | location of spline knots. If `NULL`, an incidence matrix representation will be used. See ‘Details’
`zeroIntercept` | experimental feature. If `TRUE`, the fitted values of the fixed- and random-effects functions at the intercept will be zero
`deltaEM` | convergence tolerance for the EM algorithm
`deltaNM` | (relative) convergence tolerance for the Nelder-Mead optimisation
`criteria` | one of `"AICc"`, `"AIC"`, `"BICN"` or `"BICn"` indicating which criteria to use to score a particular combination of `lambda.mu` and `lambda.v` in the Nelder-Mead search
`numberOfThreads` | The number of threads to use to fit the multiple smoothing-splines mixed-effects models simultaneously. When `numberOfThreads=-1`, as is the default, the OpenMP system will handle thread creation dynamically
`...` | additional arguments, currently not used

### Details

The default behaviour is to use an incidence matrix representation for the smoothing-splines. This works well in most situations but may incur a high computational cost when the number of distinct time points is large, as may be the case for irregularly sampled data. Alternatively, a basis projection can be used by giving a vector of `knots` of length (much) less than the number of distinct time points.

### Value

A list of objects of class `sme`. See `smeObject` for the components of the fit and `plot.sme` for visualisation options

### Author(s)

Maurice Berk maurice@mauriceberk.com

### References

Berk, M. (2012). Smoothing-splines Mixed-effects Models in R. Preprint

### See Also

`smeObject`, `sme`, `sme.data.frame`, `plot.sme`

[Package sme version 0.8 Index]