unpack_slope

Makes A list of terms and applies unpack_slope_term() to each of them. Then builds the code for this segment's slope

internal

Flexible and informed regression with Multiple Change Points. 'mcp' can infer change points in means, variances, autocorrelation structure, and any combination of these, as well as the parameters of the segments in between. All parameters are estimated with uncertainty and prediction intervals are supported - also near the change points. 'mcp' supports hypothesis testing via Savage-Dickey density ratio, posterior contrasts, and cross-validation. 'mcp' is described in Lindeløv (submitted) <doi:10.31219/osf.io/fzqxv> and generalizes the approach described in Carlin, Gelfand, & Smith (1992) <doi:10.2307/2347570> and Stephens (1994) <doi:10.2307/2986119>.

Jonas Kristoffer Lindel<c3><b8>v

Regression with Multiple Change Points

Jonas Kristoffer Lindeløv

unpack_slope function

<dl><dt>form</dt>
<dd>A formula</dd>
<dt>i</dt>
<dd>Segment number (integer)</dd>
<dt>ttype</dt>
<dd>The term type. One of "ct" (central tendency), "sigma" (variance),
or "ar" (autoregressive)</dd>
<dt>last_slope</dt>
<dd>The element in the slope column for this ttype in the previous
segment. I.e., probably what this function returned last time it was called!</dd></dl>

Arguments

Jonas Kristoffer Lindeløv <a href="/link/jonas%40lindeloev.dk?package=mcp&version=0.3.3" data-mini-rdoc="mcp::jonas@lindeloev.dk">jonas@lindeloev.dk</a>

Author

Unpack the slope of a formula — unpack_slope

<dl>

<dt>form</dt>
<dd>A formula</dd>


<dt>i</dt>
<dd>Segment number (integer)</dd>


<dt>ttype</dt>
<dd>The term type. One of "ct" (central tendency), "sigma" (variance),
or "ar" (autoregressive)</dd>


<dt>last_slope</dt>
<dd>The element in the slope column for this ttype in the previous
segment. I.e., probably what this function returned last time it was called!</dd>

</dl>

Jonas Kristoffer Lindeløv <a href='mailto:jonas@lindeloev.dk'>jonas@lindeloev.dk</a>

unpack_slope: Unpack the slope of a formula

Description

Usage

Value

Arguments

Author