<!doctype s-function-doc system "s-function-doc.dtd" [
<!entity % S-OLD "INCLUDE">
]
>
<s-function-doc>
<s-topics>
   <s-topic>lmRobBI.control</s-topic>
</s-topics>
<s-title>
Control Parameters for Bounded Influence Robust Regression 
</s-title>
<s-description>
Allows the users to set values affecting the estimation procedure for robust  
regression in <s-expression>lmRobBI</s-expression>. 
</s-description>
<s-usage>
<s-old-style-usage>
lmRobBI.control(efficiency=0.95, tuning.p=NULL, max.wt=150, max.rg=30,  
alg="W", tol=1e-05, tau=1e-11) 
</s-old-style-usage>
</s-usage>
<s-args-optional>
<s-arg name="efficiency">
the asymptotic efficiency of the bounded influence estimates. 
</s-arg>
<s-arg name="tuning.p">
a scalar which gives the value of the tuning constant for the  
psi-function of the corresponding generalized M-estimator. It is 
only used if <s-expression>method="mal"</s-expression>. 
</s-arg>
<s-arg name="max.wt">
the maximum number of iterations to compute the optimal weights. 
</s-arg>
<s-arg name="max.rg">
the maximum number of iterations to compute the regression estimates. 
</s-arg>
<s-arg name="alg">
specifies the algorithm which will be used to compute the regression 
estimates. If <s-expression>alg="W"</s-expression>, the conjugate gradient algorithm will be used;  
if <s-expression>alg="N"</s-expression>, the Newton-Huber algorithm will be used.  
</s-arg>
<s-arg name="tol">
the relative tolerance in the iterative algorithms. 
</s-arg>
<s-arg name="tau">
the tolerance used for the determination of pseudo-rank. 
</s-arg>
</s-args-optional>
<s-value>
a list containing the values used for each of the control parameters. 
</s-value>
<s-see>
<s-function name="lmRobBI.sgm">lmRobBI</s-function>. </s-see>
<s-examples>
<s-example type = text>
control.95 <- lmRobBI.control(efficiency=0.85) 
</s-example>
</s-examples>
<s-keywords>
<s-keyword>librobust</s-keyword>
</s-keywords>
<s-docclass>
function
</s-docclass>
</s-function-doc>
