R: Fitter Functions for Segmented Linear Models

seg.lm.fit {segmented} | R Documentation

## Fitter Functions for Segmented Linear Models

### Description

`seg.lm.fit` is called by `segmented.lm` to fit segmented linear (gaussian) models. Likewise, `seg.glm.fit` is called by `segmented.glm` to fit generalized segmented linear models, and `seg.def.fit` is called by `segmented.default` to fit segmented relationships in general regression models (e.g., quantile regression and Cox regression). `seg.lm.fit.boot`, `seg.glm.fit.boot`, and `seg.def.fit.boot` are employed to perform bootstrap restart. These functions should usually not be used directly by the user.

### Usage

    seg.lm.fit(y, XREG, Z, PSI, w, offs, opz, return.all.sol=FALSE)

    seg.lm.fit.boot(y, XREG, Z, PSI, w, offs, opz, n.boot=10,
        size.boot=NULL, jt=FALSE, nonParam=TRUE, random=FALSE)

    seg.glm.fit(y, XREG, Z, PSI, w, offs, opz, return.all.sol=FALSE)

    seg.glm.fit.boot(y, XREG, Z, PSI, w, offs, opz, n.boot=10,
        size.boot=NULL, jt=FALSE, nonParam=TRUE, random=FALSE)

    seg.def.fit(obj, Z, PSI, mfExt, opz, return.all.sol=FALSE)

    seg.def.fit.boot(obj, Z, PSI, mfExt, opz, n.boot=10, size.boot=NULL,
        jt=FALSE, nonParam=TRUE, random=FALSE)

    seg.Ar.fit(obj, XREG, Z, PSI, opz, return.all.sol=FALSE)

    seg.Ar.fit.boot(obj, XREG, Z, PSI, opz, n.boot=10, size.boot=NULL, jt=FALSE,
        nonParam=TRUE, random=FALSE)

### Arguments

`y` | vector of observations of length `n`.
`XREG` | design matrix for standard linear terms.
`Z` | appropriate matrix including the segmented variables whose breakpoints have to be estimated.
`PSI` | appropriate matrix including the starting values of the breakpoints to be estimated.
`w` | possibe weights vector.
`offs` | possibe offset vector.
`opz` | a list including information useful for model fitting.
`n.boot` | the number of bootstrap samples employed in the bootstrap restart algorithm.
`size.boot` | the size of the bootstrap resamples. If `NULL` (default), it is taken equal to the sample size. values smaller than the sample size are expected to increase perturbation in the bootstrap resamples.
`jt` | logical. If `TRUE` the values of the segmented variable(s) are jittered before fitting the model to the bootstrap resamples.
`nonParam` | if `TRUE` nonparametric bootstrap (i.e. case-resampling) is used, otherwise residual-based.
`random` | if `TRUE`, when the algorithm fails to obtain a solution, random values are used as candidate values.
`return.all.sol` | if `TRUE`, when the algorithm fails to obtain a solution, the values visited by the algorithm with corresponding deviances are returned.
`obj` | the starting regression model where the segmented relationships have to be added.
`mfExt` | the model frame.

### Details

The functions call iteratively `lm.wfit` (or `glm.fit`) with proper design matrix depending on `XREG`, `Z` and `PSI`. `seg.lm.fit.boot` (and `seg.glm.fit.boot`) implements the bootstrap restarting idea discussed in Wood (2001).

### Value

A list of fit information.

### Note

These functions should usually not be used directly by the user.

### Author(s)

Vito Muggeo

### References

Wood, S. N. (2001) Minimizing model fitting objectives that contain spurious local minima by bootstrap restarting. Biometrics 57, 240–244.

### See Also

`segmented.lm`, `segmented.glm`

### Examples

    ##See ?segmented

[Package segmented version 0.5-3.0 Index]