my_e2truncnorm

Computes the expected squared values 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_e2truncnorm 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 square of the untruncated mean is returned if it lies 
within <code>[a, b]</code> and the square of the nearer of <code>a</code> and 
<code>b</code> is returned otherwise.</dd></dl>

Arguments

Expected Squared Value of Truncated Normal — my_e2truncnorm

<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 square of the untruncated mean is returned if it lies 
within <code>[a, b]</code> and the square of the nearer of <code>a</code> and 
<code>b</code> is returned otherwise.</dd>

</dl>

Expected Squared Value of Truncated Normal

my_e2truncnorm: Expected Squared Value of Truncated Normal

Description

Usage

Value

Arguments

See Also