Estimates the three parameters of a mixture of two exponential
 distributions by maximum likelihood estimation.

mix2exp

An implementation of about 6 major classes of
statistical regression models. The central algorithm is
Fisher scoring and iterative reweighted least squares.
At the heart of this package are the vector generalized linear
and additive model (VGLM/VGAM) classes. VGLMs can be loosely
thought of as multivariate GLMs. VGAMs are data-driven
VGLMs that use smoothing. The book "Vector Generalized
Linear and Additive Models: With an Implementation in R"
(Yee, 2015) <DOI:10.1007/978-1-4939-2818-7> gives details of
the statistical framework and the package. Currently only
fixed-effects models are implemented. Many (100+) models and
distributions are estimated by maximum likelihood estimation
(MLE) or penalized MLE. The other classes are RR-VGLMs
(reduced-rank VGLMs), quadratic RR-VGLMs, doubly constrained
RR-VGLMs, quadratic RR-VGLMs, reduced-rank VGAMs,
RCIMs (row-column interaction models)---these classes perform
constrained and unconstrained quadratic ordination (CQO/UQO)
models in ecology, as well as constrained additive ordination
(CAO). Hauck-Donner effect detection is implemented.
Note that these functions are subject to change;
see the NEWS and ChangeLog files for latest changes.

Thomas Yee

VGAM

Vector Generalized Linear and Additive Models

Cleve Moler

mix2exp function

Mixture of Two Exponential Distributions — mix2exp

<dl>

 <dt>lphi, llambda</dt>
<dd>Link functions for the parameters \(\phi\)
 and \(\lambda\). The latter is the rate parameter
 and note that the mean of an ordinary exponential distribution is
 \(1 / \lambda\).
 See <code>Links</code> for more choices.
</dd>


 <dt>iphi, il1, il2</dt>
<dd>Initial value for \(\phi\), and
 optional initial value for \(\lambda_1\) and
 \(\lambda_2\).
 The last two have values that must be positive.
 The default is to compute initial values internally using
 the argument <code>qmu</code>.
</dd>

 <dt>qmu</dt>
<dd>Vector with two values giving the probabilities relating to the
 sample quantiles for obtaining initial values for
 \(\lambda_1\) and \(\lambda_2\). The two
 values are fed in as the <code>probs</code> argument into
 <code><a href='https://rdrr.io/r/stats/quantile.html'>quantile</a></code>.
</dd>

 <dt>nsimEIM, zero</dt>
<dd>See <code>CommonVGAMffArguments</code>.

</dd>

</dl>

Arguments

This VGAM family function requires care for a successful
 application.
 In particular, good initial values are required because
 of the presence of local solutions. Therefore running
 this function with several different combinations of
 arguments such as <code>iphi</code>, <code>il1</code>, <code>il2</code>,
 <code>qmu</code> is highly recommended. Graphical methods such
 as <code><a href='https://rdrr.io/r/graphics/hist.html'>hist</a></code> can be used as an aid.

This VGAM family function is experimental and
 should be used with care.

mix2exp: Mixture of Two Exponential Distributions

Description

Usage

Arguments

Value

Details

See Also

Examples