unpack_slope_term

Returns a row for <code>unpack_slope()</code>.

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_term function

<dl><dt>term</dt>
<dd>A character, e.g., "x", "I(x^2)", or "log(x)".</dd>
<dt>i</dt>
<dd>Segment number (integer)</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>
<dt>ttype</dt>
<dd>The term type. One of "ct" (central tendency), "sigma" (variance),
or "ar" (autoregressive)</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

Unpacks a single term — unpack_slope_term

<dl>

<dt>term</dt>
<dd>A character, e.g., "x", "I(x^2)", or "log(x)".</dd>


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


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

</dl>

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

unpack_slope_term: Unpacks a single term

Description

Usage

Value

Arguments

Author