학술논문

The Profiled Feldman-Cousins technique for confidence interval construction in the presence of nuisance parameters
Document Type
Working Paper
Author
Acero, M. A.Acharya, B.Adamson, P.Aliaga, L.Anfimov, N.Antoshkin, A.Arrieta-Diaz, E.Asquith, L.Aurisano, A.Back, A.Backhouse, C.Baird, M.Balashov, N.Baldi, P.Bambah, B. A.Bashar, S.Bat, A.Bays, K.Bernstein, R.Bhatnagar, V.Bhattarai, D.Bhuyan, B.Bian, J.Booth, A. C.Bowles, R.Brahma, B.Bromberg, C.Buchanan, N.Butkevich, A.Calvez, S.Carroll, T. J.Catano-Mur, E.Chatla, A.Chirco, R.Choudhary, B. C.Choudhary, S.Christensen, A.Coan, T. E.Colo, M.Cremonesi, L.Davies, G. S.Derwent, P. F.Ding, P.Djurcic, Z.Dolce, M.Doyle, D.Tonguino, D. DueñasDukes, E. C.Dye, A.Ehrlich, R.Elkins, M.Ewart, E.Feldman, G. J.Filip, P.Franc, J.Frank, M. J.Gallagher, H. R.Gandrajula, R.Gao, F.Giri, A.Gomes, R. A.Goodman, M. C.Grichine, V.Groh, M.Group, R.Guo, B.Habig, A.Hakl, F.Hall, A.Hartnell, J.Hatcher, R.Hausner, H.He, M.Heller, K.Hewes, VHimmel, A.Jargowsky, B.Jarosz, J.Jediny, F.Johnson, C.Judah, M.Kakorin, I.Kaplan, D. M.Kalitkina, A.Kleykamp, J.Klimov, O.Koerner, L. W.Kolupaeva, L.Kotelnikov, S.Kralik, R.Kullenberg, Ch.Kubu, M.Kumar, A.Kuruppu, C. D.Kus, V.Lackey, T.Lang, K.Lasorak, P.Lesmeister, J.Lin, S.Lister, A.Liu, J.Lokajicek, M.Lopez, J. M. C.Mahji, R.Magill, S.Plata, M. ManriqueMann, W. A.Manoharan, M. T.Marshak, M. L.Martinez-Casales, M.Matveev, V.Mayes, B.Mehta, B.Messier, M. D.Meyer, H.Miao, T.Mikola, V.Miller, W. H.Mishra, S.Mishra, S. R.Mislivec, A.Mohanta, R.Moren, A.Morozova, A.Mu, W.Mualem, L.Muether, M.Mulder, K.Naples, D.Nath, A.Nayak, N.Nelleri, S.Nelson, J. K.Nichol, R.Niner, E.Norman, A.Norrick, A.Nosek, T.Oh, H.Olshevskiy, A.Olson, T.Ott, J.Pal, A.Paley, J.Panda, L.Patterson, R. B.Pawloski, G.Pershey, D.Petrova, O.Petti, R.Phan, D. D.Plunkett, R. K.Pobedimov, A.Porter, J. C. C.Rafique, A.Prais, L. R.Raj, V.Rajaoalisoa, M.Ramson, B.Rebel, B.Rojas, P.Roy, P.Ryabov, V.Samoylov, O.Sanchez, M. C.Falero, S. SánchezShanahan, P.Sharma, P.Shukla, S.Sheshukov, A.Singh, I.Singh, P.Singh, V.Smith, E.Smolik, J.Snopok, P.Solomey, N.Sousa, A.Soustruznik, K.Strait, M.Suter, L.Sutton, A.Swain, S.Sweeney, C.Sztuc, A.Oregui, B. TapiaTas, P.Temizel, B. N.Thakore, T.Thayyullathil, R. B.Thomas, J.Tiras, E.Tripathi, J.Trokan-Tenorio, J.Torun, Y.Urheim, J.Vahle, P.Vallari, Z.Vasel, J.Vrba, T.Wallbank, M.Warburton, T. K.Wetstein, M.Whittington, D.Wickremasinghe, D. A.Wieber, T.Wolcott, J.Wrobel, M.Wu, W.Xiao, Y.Yaeggy, B.Dombara, A. YallappaYankelevich, A.Yonehara, K.Yu, S.Yu, Y.Zadorozhnyy, S.Zalesak, J.Zhang, Y.Zwaska, R.
Source
Subject
High Energy Physics - Experiment
Physics - Data Analysis, Statistics and Probability
Language
Abstract
Measuring observables to constrain models using maximum-likelihood estimation is fundamental to many physics experiments. The Profiled Feldman-Cousins method described here is a potential solution to common challenges faced in constructing accurate confidence intervals: small datasets, bounded parameters, and the need to properly handle nuisance parameters. This method achieves more accurate frequentist coverage than other methods in use, and is generally applicable to the problem of parameter estimation in neutrino oscillations and similar measurements. We describe an implementation of this method in the context of the NOvA experiment.
Comment: 19 pages, 12 figures