R help - Dec 2011 - hi all.regarding quantile regression results..

i know this is not about R.
After applying quantile regression with t=0.5,0.6  on the data set WBC(
Wisconsin Breast Cancer)with 678 observations and 9 independent
variables(inp1,inp2,...inp9) and 1 dependent variable(op)  i have got the 
following results for beta values.

when t=0.5(median regression) beta values   b1=0.002641,b2=0.045746,b3=0.
005282,b4=0.004397,b5=0.002641,b6=0.065807,b7=0.005282
,b8=0.031394,b9=0.004993 and intercept is -0.181388

and when t=0.6 beta values are
b1=0,b2=0.01,b3=0,b4=-0.002,b5=0.004,b6=0.1111,b7=0.002,b8=0,b9=0 and
intercept is -0.009 .

 sir,how to interpret the above beta coefficients and what do they mean
exactly??.
t=0.5 means are we considering first 50% of the total data?
t=0.6 means are we considering the first 60% of the total data?
 can we write a equation like

 
y=intercept+b1*inp11+b2*inp29+b3*inp3+b4*inp4+b5*inp5+b6*inp6+b7*inp7+b8*inp8+b9*inp9
as in Linear Regression
to calculate the predicted output of y or not??

 If we are taking  into  consideration 5 quantiles of data ,Does it  mean
that we are dividing data it into 5 parts??which variables i have to
consider if the data is to be divided into 5 parts?

And
  i got  5 equations for 5 quantiles, what exactly each equation represents?
  Can i write single equation for the data set as in mean regression by
combining the 5 equations of each quantile.
Please reply me.

Thanks In advance,

    With regards

Kalam Naerndar Reddy
    M.Tech(IT),
University of Hyderabad.

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This really isn't the appropriate forum for most of your questions: I'd
suggest you work through the Wikipedia article on quantiles regression and
direct follow up to stats.stackexchange.com.

As to the R question: use the predict() function. 

Michael

On Dec 1, 2011, at 8:12 AM, narendarreddy kalam <narendarcse007 at
gmail.com> wrote:
> i know this is not about R.
> After applying quantile regression with t=0.5,0.6  on the data set WBC(
> Wisconsin Breast Cancer)with 678 observations and 9 independent
> variables(inp1,inp2,...inp9) and 1 dependent variable(op)  i have got the 
> following results for beta values.
> 
> when t=0.5(median regression) beta values   b1=0.002641,b2=0.045746,b3=0.
> 005282,b4=0.004397,b5=0.002641,b6=0.065807,b7=0.005282
> ,b8=0.031394,b9=0.004993 and intercept is -0.181388
> 
> and when t=0.6 beta values are
> b1=0,b2=0.01,b3=0,b4=-0.002,b5=0.004,b6=0.1111,b7=0.002,b8=0,b9=0 and
> intercept is -0.009 .
> 
> sir,how to interpret the above beta coefficients and what do they mean
> exactly??.
> t=0.5 means are we considering first 50% of the total data?
> t=0.6 means are we considering the first 60% of the total data?
> can we write a equation like
> 
> 
>
y=intercept+b1*inp11+b2*inp29+b3*inp3+b4*inp4+b5*inp5+b6*inp6+b7*inp7+b8*inp8+b9*inp9
> as in Linear Regression
> to calculate the predicted output of y or not??
> 
> If we are taking  into  consideration 5 quantiles of data ,Does it  mean
> that we are dividing data it into 5 parts??which variables i have to
> consider if the data is to be divided into 5 parts?
> 
> And
>  i got  5 equations for 5 quantiles, what exactly each equation represents?
>  Can i write single equation for the data set as in mean regression by
> combining the 5 equations of each quantile.
> Please reply me.
> 
> Thanks In advance,
> 
>    With regards
> 
> Kalam Naerndar Reddy
>    M.Tech(IT),
> University of Hyderabad.
> 
> --
> View this message in context:
http://r.789695.n4.nabble.com/hi-all-regarding-quantile-regression-results-tp4128248p4128248.html
> Sent from the R help mailing list archive at Nabble.com.
> 
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