my_etruncnorm

Computes the means of truncated normal distributions with
 parameters <code>a</code>, <code>b</code>, <code>mean</code>, and <code>sd</code>. Arguments
 can be scalars, vectors, or matrices. Arguments of shorter length will
 be recycled according to the usual recycling rules, but <code>a</code> and 
 <code>b</code> must have the same length. Missing values are accepted for all 
 arguments.

The R package 'ashr' implements an Empirical Bayes
approach for large-scale hypothesis testing and false discovery
rate (FDR) estimation based on the methods proposed in
M. Stephens, 2016, "False discovery rates: a new deal",
<DOI:10.1093/biostatistics/kxw041>. These methods can be applied
whenever two sets of summary statistics---estimated effects and
standard errors---are available, just as 'qvalue' can be applied
to previously computed p-values. Two main interfaces are
provided: ash(), which is more user-friendly; and ash.workhorse(),
which has more options and is geared toward advanced users. The
ash() and ash.workhorse() also provides a flexible modeling
interface that can accommodate a variety of likelihoods (e.g.,
normal, Poisson) and mixture priors (e.g., uniform, normal).

Peter Carbonetto

ashr

Methods for Adaptive Shrinkage, using Empirical Bayes

Matthew Stephens

Chaoxing Dai

David Gerard

Mengyin Lu

Lei Sun

Jason Willwerscheid

Nan Xiao

Mazon Zeng

my_etruncnorm function

<dl><dt>a</dt>
<dd>The lower limit for the support of the truncated normal. Can be
<code>-Inf</code>.</dd>
<dt>b</dt>
<dd>The upper limit for the support. Can be <code>Inf</code>. <code>a</code> and 
<code>b</code> must have the same length, and each element of <code>a</code> should 
be less than or equal to the corresponding element of <code>b</code>.</dd>
<dt>mean</dt>
<dd>The mean of the untruncated normal.</dd>
<dt>sd</dt>
<dd>The standard deviation of the untruncated normal. Standard
deviations of zero are interpreted as numerically (rather than exactly)
zero, so that the untruncated mean is returned if it lies within 
<code>[a, b]</code> and the nearer of <code>a</code> and <code>b</code> is returned
otherwise.</dd></dl>

Arguments

Expected Value of Truncated Normal — my_etruncnorm

<dl>

<dt>a</dt>
<dd>The lower limit for the support of the truncated normal. Can be
<code>-Inf</code>.</dd>


<dt>b</dt>
<dd>The upper limit for the support. Can be <code>Inf</code>. <code>a</code> and 
<code>b</code> must have the same length, and each element of <code>a</code> should 
be less than or equal to the corresponding element of <code>b</code>.</dd>


<dt>mean</dt>
<dd>The mean of the untruncated normal.</dd>


<dt>sd</dt>
<dd>The standard deviation of the untruncated normal. Standard
deviations of zero are interpreted as numerically (rather than exactly)
zero, so that the untruncated mean is returned if it lies within 
<code>[a, b]</code> and the nearer of <code>a</code> and <code>b</code> is returned
otherwise.</dd>

</dl>

Expected Value of Truncated Normal

my_etruncnorm: Expected Value of Truncated Normal

Description

Usage

Value

Arguments

See Also