model.matrix.stepmented

This function builds the model matrix for <code>stepmented</code> fits.

Fitting regression models where, in addition to possible linear terms, one or more covariates have segmented (i.e., broken-line or piece-wise linear) or stepmented (i.e. piece-wise constant) effects.
Multiple breakpoints for the same variable are allowed. The estimation method is discussed in Muggeo (2003, <doi:10.1002/sim.1545>) and
illustrated in Muggeo (2008, <https://www.r-project.org/doc/Rnews/Rnews_2008-1.pdf>). An approach for hypothesis testing is presented
in Muggeo (2016, <doi:10.1080/00949655.2016.1149855>), and interval estimation for the breakpoint is discussed in Muggeo (2017, <doi:10.1111/anzs.12200>).
Segmented mixed models, i.e. random effects in the change point, are discussed in Muggeo (2014, <doi:10.1177/1471082X13504721>).
Estimation of piecewise-constant relationships and changepoints (mean-shift models) is
discussed in Fasola et al. (2018, <doi:10.1007/s00180-017-0740-4>).

Vito MR Muggeo

segmented

Regression Models with Break-Points / Change-Points Estimation
(with Possibly Random Effects)

model.matrix.stepmented function

<dl> <dt>object</dt>
<dd>A stepmented fit</dd> <dt>k</dt>
<dd>The (negative) exponent of the sample size to approximate the absolute value; see <code>vcov.stepmented</code></dd> <dt>apprx</dt>
<dd>The approximation of the absolute value.</dd> <dt>...</dt>
<dd>additional arguments</dd></dl>

Arguments

Author

Design matrix for stepmented fits — model.matrix.stepmented

<dl>

 <dt>object</dt>
<dd>A stepmented fit</dd>

 <dt>k</dt>
<dd>The (negative) exponent of the sample size to approximate the absolute value; see <code>vcov.stepmented</code></dd>

 <dt>apprx</dt>
<dd>The approximation of the absolute value.</dd>

 <dt>...</dt>
<dd>additional arguments</dd>

</dl>

model.matrix.stepmented: Design matrix for stepmented fits

Description

Usage

Value

Arguments

Author

Details

See Also