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Combined Neyman–Pearson chi-square: An improved approximation to the Poisson-likelihood chi-square

Journal Article · · Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment
We describe an approximation to the widely-used Poisson-likelihood chi-square using a linear combination of Neyman’s and Pearson’s chi-squares, namely “combined Neyman–Pearson chi-square” ($$X^2_{CNP}$$). Through analytical derivations and toy model simulations, we show that leads to a significantly smaller bias on the best-fit model parameters compared to those using either Neyman’s or Pearson’s chi-square. When the computational cost of using the Poisson-likelihood chi-square is high, $$X^2_{CNP}$$ provides a good alternative given its natural connection to the covariance matrix formalism.
Research Organization:
Brookhaven National Laboratory (BNL), Upton, NY (United States)
Sponsoring Organization:
USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25)
Grant/Contract Number:
SC0012704
OSTI ID:
1603273
Alternate ID(s):
OSTI ID: 1601521
Report Number(s):
BNL--213688-2020-JAAM
Journal Information:
Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment, Journal Name: Nuclear Instruments and Methods in Physics Research. Section A, Accelerators, Spectrometers, Detectors and Associated Equipment Journal Issue: C Vol. 961; ISSN 0168-9002
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English

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