| Year |
Citation |
Score |
| 2019 |
Cisewski-Kehe J, Weller G, Schafer C. A preferential attachment model for the stellar initial mass function Electronic Journal of Statistics. 13: 1580-1607. DOI: 10.1214/19-Ejs1556 |
0.433 |
|
| 2019 |
Wang K, Mao Y, Zentner AR, Bosch FCvd, Lange JU, Schafer CM, Villarreal AS, Hearin AP, Campbell D. How to optimally constrain galaxy assembly bias: supplement projected correlation functions with count-in-cells statistics Monthly Notices of the Royal Astronomical Society. 488: 3541-3567. DOI: 10.1093/Mnras/Stz1733 |
0.306 |
|
| 2019 |
Metcalf RB, Meneghetti M, Avestruz C, Bellagamba F, Bom CR, Bertin E, Cabanac R, Courbin F, Davies A, Decencière E, Flamary R, Gavazzi R, Geiger M, Hartley P, Huertas-Company M, et al. The Strong Gravitational Lens Finding Challenge Astronomy and Astrophysics. 625. DOI: 10.1051/0004-6361/201832797 |
0.387 |
|
| 2015 |
Schafer CM. A Framework for Statistical Inference in Astrophysics Annual Review of Statistics and Its Application. 2: 141-162. DOI: 10.1146/annurev-statistics-022513-115538 |
0.326 |
|
| 2014 |
Izbicki R, Lee AB, Schafer CM. High-dimensional density ratio estimation with extensions to approximate likelihood computation Journal of Machine Learning Research. 33: 420-429. |
0.339 |
|
| 2013 |
Weyant A, Schafer C, Wood-Vasey WM. Likelihood-free cosmological inference with type ia supernovae: Approximate bayesian computation for a complete treatment of uncertainty Astrophysical Journal. 764. DOI: 10.1088/0004-637X/764/2/116 |
0.422 |
|
| 2013 |
Schafer CM, Freeman PE. Likelihood-free inference in cosmology: Potential for the estimation of luminosity functions Information Systems Development: Reflections, Challenges and New Directions. 3-19. DOI: 10.1007/978-1-4614-3520-4-1 |
0.392 |
|
| 2012 |
Richards JW, Homrighausen D, Freeman PE, Schafer CM, Poznanski D. Semi-supervised learning for photometric supernova classification Monthly Notices of the Royal Astronomical Society. 419: 1121-1135. DOI: 10.1111/J.1365-2966.2011.19768.X |
0.35 |
|
| 2011 |
Buchman SM, Lee AB, Schafer CM. High-dimensional density estimation via SCA: An example in the modelling of hurricane tracks Statistical Methodology. 8: 18-30. DOI: 10.1016/J.Stamet.2009.07.002 |
0.382 |
|
| 2010 |
Richards JW, Lee AB, Schafer CM, Freeman PE. Prototype selection for parameter estimation in complex models Annals of Applied Statistics. 4: 383-408. DOI: 10.1214/11-Aoas500 |
0.455 |
|
| 2009 |
Schafer CM, Stark PB. Constructing confidence regions of optimal expected size Journal of the American Statistical Association. 104: 1080-1089. DOI: 10.1198/Jasa.2009.Tm07420 |
0.515 |
|
| 2009 |
Richards JW, Freeman PE, Lee AB, Schafer CM. Accurate parameter estimation for star formation history in galaxies using SDSS spectra Monthly Notices of the Royal Astronomical Society. 399: 1044-1057. DOI: 10.1111/J.1365-2966.2009.15349.X |
0.434 |
|
| 2009 |
Freeman PE, Newman JA, Lee AB, Richards JW, Schafer CM. Photometric redshift estimation using spectral connectivity analysis Monthly Notices of the Royal Astronomical Society. 398: 2012-2021. DOI: 10.1111/J.1365-2966.2009.15236.X |
0.438 |
|
| 2009 |
Richards JW, Freeman PE, Lee AB, Schafer CM. Exploiting Low-Dimensional Structure In Astronomical Spectra The Astrophysical Journal. 691: 32-42. DOI: 10.1088/0004-637X/691/1/32 |
0.339 |
|
| 2009 |
Schafer CM, Doksum KA. Selecting local models in multiple regression by maximizing power Metrika. 69: 283-304. DOI: 10.1007/S00184-008-0218-Z |
0.409 |
|
| 2008 |
Freeman P, Richards J, Schafer C, Lee A. Astrostatistics: The final frontier Chance. 21: 31-35. DOI: 10.1007/S144-008-0026-2 |
0.427 |
|
| 2007 |
Bryan B, McMahan HB, Schafer CM, Schneider J. Efficiently computing minimax expected-size confidence regions Acm International Conference Proceeding Series. 227: 97-104. DOI: 10.1145/1273496.1273509 |
0.31 |
|
| 2007 |
Schafer CM. A statistical method for estimating luminosity functions using truncated data Astrophysical Journal. 661: 703-713. DOI: 10.1086/515390 |
0.402 |
|
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