[gradsusr] Referencing a Student Distribution Table inside Grads for Calculating confidence level from varying Effective N and varying T Value.

[Arlindo da Silva]

Dear Muhammad,

  Consult the documentation for the opengrads BJT extension for t-test and
other functionality currently available:

             http://opengrads.org/doc/udxt/libbjt/

   Arlindo


On Wed, Jun 11, 2014 at 3:21 AM, Muhammad Yunus Ahmad Mazuki <
ukm.yunus at gmail.com> wrote:

> Hi,
>
> I have a question here. How do I reference a Students Distribution Table
> inside GraDS? I will explain my situation here. Using GraDS scripting, I
> was able to calculate slope, and intercept from linear regression
> calculation. Using the slope and intercept I was able to construct a fitted
> model and find the standard error of the slope. From which I calculate
> residuals (simply the data minus fitted model), finding actop and acbottom,
> then residual auto correlation (actop divide by acbottom). Depending on the
> value of the residual autocorrelation, I calculate Effective N to be either
> the original n or based on calculation using the residual auto correlation.
> After which I find the standard error based on effective n. Then finally t
> value from dividing the standard error of the slope with the standard error
> based on effective n. What I need to do next is to get the corresponding
> confidence level by using the calculated t value and effective n to a
> student distribution table. How do I go about this? Below is flow of the
> calculation.
>
> 1. Calculate 30 JJA seasons of a variable (produce time1 until time30)
> 2. Calculate the slope and intercept using linear regression (produce
> slope and intercept)
> 3. Calculate the fitted model using the intercept and and slope (produce
> fitted1 to fitted30)
> 4. Calculate the standard error of the slope(SEOTS) (produced SEOTS)
> 5. Calculate the residuals, time-fitted (produce residual1 to residual30)
> 6. Calculate the residual mean.
> 7. Calculate actop
> 8. Calculate acbottom
> 9. Calculate the residual auto correlation
> 10. based on value of residual auto correlation, calculate effective n
> 11. Effective n is either 30 (in this example) or through calculation.
> 12. Calculate the standard error based on effective n
> 13. Calculate Tvalue which is slope divided by standard error based on
> effective n
>
> This is where I'm stuck. I want to reference a students distribution table
> to get the confidence level for the slope (which is actually trend of
> linear regression). And the confidence level varies between each grid point
> as the t value and effective n varies between each grid point.
>
> In Scilab 5.5.0, I would use:
> [p,q]=cdft('pq',abs(TValue),round(EffectiveN+0.5))
> ConfidenceLevel=(1-(q*2))*100
> which will give the confidence value from double tailed t test. This is
> just an example. Is there any student distribution function inside GraDS
> which I'm not aware of?
>
> So how do I do this with GraDS or openGraDS?
>
>
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>


-- 
Arlindo da Silva
*dasilva at alum.mit.edu <dasilva at alum.mit.edu>*
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