.hurdle_default_starts

Internal function to generate sensible default starting values for TMB
hurdle model optimization.

internal

Facilitates many of the analyses performed in studies of
behavioral economic demand. The package supports commonly-used options for
modeling operant demand including (1) data screening proposed by Stein,
Koffarnus, Snider, Quisenberry, & Bickel (2015; <doi:10.1037/pha0000020>),
(2) fitting models of demand such as linear (Hursh, Raslear, Bauman,
& Black, 1989, <doi:10.1007/978-94-009-2470-3_22>), exponential (Hursh & Silberberg, 2008,
<doi:10.1037/0033-295X.115.1.186>) and modified exponential (Koffarnus,
Franck, Stein, & Bickel, 2015, <doi:10.1037/pha0000045>), and (3) calculating
numerous measures relevant to applied behavioral economists (Intensity,
Pmax, Omax). Also supports plotting and comparing data.

Brent Kaplan

beezdemand

Behavioral Economic Easy Demand

Shawn Gilroy

.hurdle_default_starts function

<dl><dt>consumption</dt>
<dd>Numeric vector of consumption values.</dd>
<dt>n_re</dt>
<dd>Number of random effects (2 or 3).</dd>
<dt>n_subjects</dt>
<dd>Number of subjects.</dd>
<dt>has_k</dt>
<dd>Logical, whether the model has a k parameter.</dd></dl>

Arguments

Generate Default Starting Values for Hurdle Model — .hurdle_default_starts

<dl>

<dt>consumption</dt>
<dd>Numeric vector of consumption values.</dd>


<dt>n_re</dt>
<dd>Number of random effects (2 or 3).</dd>


<dt>n_subjects</dt>
<dd>Number of subjects.</dd>


<dt>has_k</dt>
<dd>Logical, whether the model has a k parameter.</dd>

</dl>

.hurdle_default_starts: Generate Default Starting Values for Hurdle Model

Description

Usage

Value

Arguments