coef.susie

Extract regression coefficients from susie fit

Implements methods for variable selection in linear
regression based on the "Sum of Single Effects" (SuSiE) model, as
described in Wang et al (2020) <DOI:10.1101/501114> and Zou et al
(2021) <DOI:10.1101/2021.11.03.467167>. These methods provide
simple summaries, called "Credible Sets", for accurately
quantifying uncertainty in which variables should be selected.
The methods are motivated by genetic fine-mapping applications,
and are particularly well-suited to settings where variables are
highly correlated and detectable effects are sparse. The fitting
algorithm, a Bayesian analogue of stepwise selection methods
called "Iterative Bayesian Stepwise Selection" (IBSS), is simple
and fast, allowing the SuSiE model be fit to large data sets
(thousands of samples and hundreds of thousands of variables).

Peter Carbonetto

susieR

Sum of Single Effects Linear Regression

Gao Wang

Yuxin Zou

Kaiqian Zhang

Matthew Stephens

coef.susie function

<dl><dt>object</dt>
<dd>A susie fit.</dd>
<dt>...</dt>
<dd>Additional arguments passed to the generic <code>coef</code>
method.</dd></dl>

Arguments

Extract regression coefficients from susie fit — coef.susie

<dl>

<dt>object</dt>
<dd>A susie fit.</dd>


<dt>...</dt>
<dd>Additional arguments passed to the generic <code>coef</code>
method.</dd>

</dl>

coef.susie: Extract regression coefficients from susie fit

Description

Usage

Value

Arguments