crbound_sigma

sigmasq

The Cram\'er-Rao lower bound (times <code>n</code>) on the variance for estimating the variance parameter <code>sigmasq</code> from a univariate truncated normal sample, assuming the true mean parameter <code>mu</code> is known.

Implementation of the Generalized Score Matching estimator in Yu et al. (2019) <http://jmlr.org/papers/v20/18-278.html> for non-negative graphical models (truncated Gaussian, exponential square-root, gamma, a-b models) and univariate truncated Gaussian distributions. Also includes the original estimator for untruncated Gaussian graphical models from Lin et al. (2016) <doi:10.1214/16-EJS1126>, with the addition of a diagonal multiplier.

Shiqing Yu

genscore

Generalized Score Matching Estimators

crbound_sigma function

<dl><dt>mu</dt>
<dd>The mean parameter.</dd>
<dt>sigmasq</dt>
<dd>The variance parameter.</dd></dl>

Arguments

The Cram\'er-Rao lower bound (times n) for estimating the variance parameter from a univariate truncated normal sample with known mean parameter. — crbound_sigma

<dl>

<dt>mu</dt>
<dd>The mean parameter.</dd>


<dt>sigmasq</dt>
<dd>The variance parameter.</dd>

</dl>

The Cram\'er-Rao lower bound (times <code>n</code>) for estimating the variance parameter from a univariate truncated normal sample with known mean parameter.

crbound_sigma: The Cram\'er-Rao lower bound (times `n`) for estimating the variance parameter from a univariate truncated normal sample with known mean parameter.

Description

Usage

Value

Arguments

Details