Difference between revisions of "Extreme Spread"
(Created page with "= Experimental Summary = {| class="wikitable" |- ! ! |- | Given | * set of ''n'' shots {<math> (h_1, v_1), (h_2, v_2), ..., (h_n, v_n) </math>}<br /> All of the (''h'',''v...") |
(→Experimental Summary) |
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| Assumptions | | Assumptions | ||
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− | * | + | * Ideally the shot would follow a Rayleigh Distribution |
** <math>\bar{h} \sim \mathcal{N}(\bar{h},\sigma_h^2), \bar{v} \sim \mathcal{N}(\bar{v},\sigma_v^2)</math> | ** <math>\bar{h} \sim \mathcal{N}(\bar{h},\sigma_h^2), \bar{v} \sim \mathcal{N}(\bar{v},\sigma_v^2)</math> | ||
** Horizontal and vertical dispersion are independent. | ** Horizontal and vertical dispersion are independent. | ||
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| Data transformation | | Data transformation | ||
− | | | + | | Identify two holes, <math>i, j</math> which are the farthest apart. |
− | |||
− | |||
|- | |- | ||
| Experimental Measure | | Experimental Measure | ||
− | | <math> | + | | <math>ES = \sqrt{(x_i - x_j)^2 - (y_i - y_j)^2)}</math>, |
|} | |} | ||
Revision as of 19:05, 5 June 2015
Contents
Experimental Summary
Given |
All of the (h,v) positions do not need to be known so a ragged hole will suffice. |
Assumptions |
|
Data transformation | Identify two holes, \(i, j\) which are the farthest apart. |
Experimental Measure | \(ES = \sqrt{(x_i - x_j)^2 - (y_i - y_j)^2)}\), |
Given
Assumptions
Data transformation
Experimental Measure
Outlier Tests
Theoretical \(h_{Range}\) or \(v_{Range}\) Distributions
Theoretical \(FOM\) Distribution
yada yada
Parameters Needed | |
\(PDF(r; \sigma)\) | |
\(CDF(r; \sigma)\) | |
Mode of PDF) | |
Median of PDF | |
Mean of PDF | |
Variance | |
Variance Distribution | |
(h,v) for all points? | Yes |
Symmetric about Mean? | No, skewed to larger values.
More symmetric as number of shots increases. |
Parameters Needed
Variance and Its distribution
CDF
Mode, Median, Mean
Outlier Tests
See Also
Dispersion Assumptions - A discussion of the different cases for shot dispersion
Diagonal - A different way of combing horizontal and vertical measurement