| 23 |
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//-------------------------------------------------------------------------------------------------- |
| 24 |
|
void MathUtils::CalcRatio(Double_t n1, Double_t n2, Double_t &r, Double_t &rlow, Double_t &rup, Int_t type = 0) |
| 25 |
|
{ |
| 26 |
< |
// Calculate ratio and lower/upper errors from given values using Bayes. |
| 26 |
> |
// Calculate ratio and lower/upper errors from given values using various methods, dependent on type: |
| 27 |
> |
// 0: Bayes |
| 28 |
> |
// 1: Feldman-Cousins |
| 29 |
> |
// 2: Clopper-Pearson |
| 30 |
|
|
| 31 |
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if (n1>n2) { |
| 32 |
|
Error("CalcRatio", "First value should be smaller than second: %f > %f", n1, n2); |
| 35 |
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rup = 0; |
| 36 |
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return; |
| 37 |
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} |
| 35 |
– |
|
| 38 |
|
|
| 39 |
|
if (n2 >= 1) { |
| 40 |
|
if (type == 1) { |
| 39 |
– |
r = double(n1) / double(n2); |
| 40 |
– |
|
| 41 |
|
//compute errors using Feldman-Cousins |
| 42 |
+ |
r = double(n1) / double(n2); |
| 43 |
|
FeldmanCousinsBinomialInterval fc; |
| 44 |
|
const double alpha = (1-0.682); |
| 45 |
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fc.init(alpha); |
| 48 |
|
rup = fc.upper() - r; |
| 49 |
|
|
| 50 |
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} else if (type == 2) { |
| 51 |
+ |
//compute errors using Clopper-Pearson |
| 52 |
|
r = double(n1) / double(n2); |
| 51 |
– |
|
| 53 |
|
ClopperPearsonBinomialInterval cp; |
| 54 |
|
const double alpha = (1-0.682); |
| 55 |
|
cp.init(alpha); |
| 58 |
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rup = cp.upper() - r; |
| 59 |
|
|
| 60 |
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} else { |
| 61 |
+ |
//compute using Bayes |
| 62 |
|
TH1D h1("dummy1","",1,1,2); |
| 63 |
|
h1.SetBinContent(1,n1); |
| 64 |
|
|
