<!doctype s-function-doc system "s-function-doc.dtd" [
<!entity % S-OLD "INCLUDE">
]
>
<s-function-doc>
<s-topics>
<s-topic> gammaRob.control </s-topic>
</s-topics>

<s-title>
Control for the Robust Gamma Parameter Estimator
</s-title>

<s-description>
Generates a list of control parameters for the robust gamma distribution
parameter estimator used in gammaRob.
</s-description>

<s-usage>
<s-old-style-usage>
gammaRob.control(estim, b1=1.5, b2=1.7, k=101, A=c(0, 0, 0),
                 maxta=1, maxtc=1, maxit=100, tol=0.0001, til=0.001,
                 sigma=0, alpha1=0.5, alpha2=20.5, u=0.99, beta=0.4,
                 gam=0.4, cov=T)
</s-old-style-usage>
</s-usage>

<s-args-required>
<s-arg name=" estim ">
the robust estimator used in gammaRob.  The choices are "tdmean" for the
truncated mean and "M" for the M.  The M estimator is not available
for the lognormal distribution.  Only the parameters required for this
estimator are returned.
</s-arg>
</s-args-required>


<s-section name="Parameters for the truncated mean">
<descrip>

<tag>alpha1</tag>
the regula falsi procedure (Marazzi and Ruffieux 1999) is applied to the
interval <s-expression>[alpha1, alpha2]</s-expression>.

<tag>alpha2</tag>
see alpha1.

<tag>u</tag>
the value of the tuning constant.

<tag>beta</tag>
value of Beta in the interval <s-expression>[0, 0.5]</s-expression>.

<tag>gam</tag>
value of Gamma in the interval <s-expression>[0, 0.5]</s-expression>.

<tag>tol</tag>
relative precision of alpha, sigma, and the truncation points.

<tag>cov</tag>
if TRUE an estimate of the variance of the mean is computed.
</descrip>
</s-section>

<s-section name="Parameters for the M">
<descrip>

<tag>b1</tag>
the tuning constant b1.

<tag>b2</tag>
the tuning constant b2.

<tag>k</tag>
the number of values of alpha for which Ab(alpha) and cb(alpha) must be
computed.

<tag>A</tag>
initial value of Ab(alpha).

<tag>maxta</tag>
maximum number of steps for improving Ab(alpha).

<tag>maxtc</tag>
maximum number of steps for improving cb(alpha).

<tag>maxit</tag>
maximum number of cycles of the main algorithm.

<tag>tol</tag>
desired relative precision of each element of Ab(alpha) and cb(alpha).

<tag>til</tag>
desired relative accuracy of numerical integrations.

<tag>sigma</tag>
if positive, then the only parameter fit is alpha.

<tag>cov</tag>
if TRUE the covariance matrix of the parameters is returned.
</descrip>
</s-section>

<s-value>
a list containing the control parameters for the estimator specified by
<s-expression>estim</s-expression>.
<s-value>

<s-see>
<s-function name="asymmetricRob.sgm">gammaRob</s-function>.
</s-see>

<s-examples>
<s-example type = text>
gammaRob(los, control = gammaRob.control("tdmean", tol=1e-6))
</s-example>
</s-examples>

<s-keywords>
<s-keyword>librobust</s-keyword>
</s-keywords>

<s-docclass>
function
</s-docclass>

</s-function-doc>
