marginalNLS

This function does not automatically extract marginal data and requires
model input obtained from <code>constructFormula</code>.

Response surface methods for drug synergy analysis. Available
methods include generalized and classical Loewe formulations as well as Highest
Single Agent methodology. Response surfaces can be plotted in an interactive
3-D plot and formal statistical tests for presence of synergistic effects are
available. Implemented methods and tests are described in the article
"BIGL: Biochemically Intuitive Generalized Loewe null model for prediction
of the expected combined effect compatible with partial agonism and antagonism"
by Koen Van der Borght, Annelies Tourny, Rytis Bagdziunas, Olivier Thas,
Maxim Nazarov, Heather Turner, Bie Verbist & Hugo Ceulemans (2017)
<doi:10.1038/s41598-017-18068-5>.

Maxim Nazarov

BIGL

Biochemically Intuitive Generalized Loewe Model

marginalNLS function

<dl><dt>data</dt>
<dd>Dose-response dataframe. Marginal data will be extracted from
it automatically.</dd>
<dt>transforms</dt>
<dd>Transformation functions. If non-null, <code>transforms</code> is
a list containing 5 elements, namely biological and power transformations
along with their inverse functions and <code>compositeArgs</code> which is a list
with argument values shared across the 4 functions. See vignette for more
information.</dd>
<dt>start</dt>
<dd>Starting parameter values. If not specified, they will be
obtained from <code>initialMarginal</code>.</dd>
<dt>model</dt>
<dd>List with model parameters. Typically, this is an output from
<code>constructFormula</code>.</dd>
<dt>nlsfn</dt>
<dd>Non-linear least-squares optimizer function</dd>
<dt>...</dt>
<dd>Further arguments that are passed to the optimizer function, 
such as <code>lower</code> or <code>upper</code> (for the "nlslm" method), or 
<code>control</code>.</dd></dl>

Arguments

Fit two 4-parameter log-logistic functions with non-linear least squares — marginalNLS

<dl>

<dt>data</dt>
<dd>Dose-response dataframe. Marginal data will be extracted from
it automatically.</dd>


<dt>transforms</dt>
<dd>Transformation functions. If non-null, <code>transforms</code> is
a list containing 5 elements, namely biological and power transformations
along with their inverse functions and <code>compositeArgs</code> which is a list
with argument values shared across the 4 functions. See vignette for more
information.</dd>


<dt>start</dt>
<dd>Starting parameter values. If not specified, they will be
obtained from <code>initialMarginal</code>.</dd>


<dt>model</dt>
<dd>List with model parameters. Typically, this is an output from
<code>constructFormula</code>.</dd>


<dt>nlsfn</dt>
<dd>Non-linear least-squares optimizer function</dd>


<dt>...</dt>
<dd>Further arguments that are passed to the optimizer function, 
such as <code>lower</code> or <code>upper</code> (for the "nlslm" method), or 
<code>control</code>.</dd>

</dl>

marginalNLS: Fit two 4-parameter log-logistic functions with non-linear least squares

Description

Usage

Arguments