Skip to main content
Bayesian Models for Astrophysical Data

Book description

This comprehensive guide to Bayesian methods in astronomy enables hands-on work by supplying complete R, JAGS, Python, and Stan code, to use directly or to adapt. It begins by examining the normal model from both frequentist and Bayesian perspectives and then progresses to a full range of Bayesian generalized linear and mixed or hierarchical models, as well as additional types of models such as ABC and INLA. The book provides code that is largely unavailable elsewhere and includes details on interpreting and evaluating Bayesian models. Initial discussions offer models in synthetic form so that readers can easily adapt them to their own data; later the models are applied to real astronomical data. The consistent focus is on hands-on modeling, analysis of data, and interpretations that address scientific questions. A must-have for astronomers, its concrete approach will also be attractive to researchers in the sciences more generally.


'This volume is a very welcome addition to the small but growing library of resources for advanced analysis of astronomical data. Astronomers are often confronted with complex constrained regression problems, situations that benefit from computationally intensive Bayesian approaches. The authors provide a unique and sophisticated guide with tutorials in methodology and software implementation. The worked examples are impressive. Many astronomers use Python and will benefit from the less familiar capabilities of R, Stan, and JAGS for Bayesian analysis. I suspect the work will also be useful to scientists in other fields who venture into the world of Bayesian computational statistics.'

Eric D. Feigelson - Pennsylvania State University, author of Modern Statistical Methods for Astronomy

'Encyclopaedic in scope, a treasure trove of ready code for the hands-on practitioner.'

Ben Wandelt - Paris Institute of Astrophysics, Institut Lagrange de Paris, Université Paris-Sorbonne

'This informative book is a valuable resource for astronomers, astrophysicists, and cosmologists at all levels of their career. From students starting out in the field to researchers at the frontiers of data analysis, everyone will find insightful techniques accompanied by helpful examples of code. With this book, Hilbe, de Souza, and Ishida are firmly taking astrostatistics into the twenty-first century.'

Roberto Trotta - Imperial College London, author of The Edge of the Sky

Refine List
Actions for selected content:
Select all | Deselect all
  • View selected items
  • Export citations
  • Download PDF (zip)
  • Send to Kindle
  • Send to Dropbox
  • Send to Google Drive
  • Send content to

    To send content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about sending content to .

    To send content to your Kindle, first ensure is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle.

    Note you can select to send to either the or variations. ‘’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

    Find out more about the Kindle Personal Document Service.

    Please be advised that item(s) you selected are not available.
    You are about to send:

Save Search

You can save your searches here and later view and run them again in "My saved searches".

Please provide a title, maximum of 40 characters.
Andreon S. and B. Weaver (2015). Bayesian Methods for the Physical Sciences: Learning from Examples in Astronomy and Physics. Springer Series in Astrostatistics. Springer.
Chattopadhyay A. K. and T. Chattopadhyay (2014). Statistical Methods for Astronomical Data Analysis. Springer Series in Astrostatistics. Springer.
Cowles M. K. (2013). Applied Bayesian Statistics: With R and OpenBUGS Examples. Springer Texts in Statistics. Springer.
Dodelson S. (2003). Modern Cosmology. Academic Press.
Feigelson E. D. and G. J. Babu (2012a). Modern Statistical Methods for Astronomy: With R Applications. Cambridge University Press.
Feigelson E. D. and G. J. Babu (2012b). Statistical Challenges in Modern Astronomy V. Lecture Notes in Statistics. Springer.
Finch W. H., J. E. Bolin, and K. Kelley (2014). Multilevel Modeling Using R. Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences. Taylor & Francis.
Gamerman D. and H. F. Lopes (2006). Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference, Second Edition. Chapman & Hall/CRC Texts in Statistical Science. Taylor & Francis.
Gelman A., J. Carlin, H. Stern, D. Dunson, A. Vehtari, and D. Rubin (2013). Bayesian Data Analysis, Third Edition. Chapman & Hall/CRC Texts in Statistical Science. Taylor & Francis.
Hardin J. W. and J. M. Hilbe (2012). Generalized Linear Models and Extensions, Third Edition. Taylor & Francis.
Hilbe J. M. (2011). Negative Binomial Regression, Second Edition. Cambridge University Press.
Hilbe J. M. (2014). Modeling Count Data. Cambridge University Press.
Hilbe J. M. (2015). Practical Guide to Logistic Regression. Taylor & Francis.
Hilbe J. M. and A. P. Robinson (2013). Methods of Statistical Model Estimation. EBL-Schweitzer. CRC Press.
Ivezić Z., A. J. Connolly, J. T. Vanderplas, and A. Gray (2014). Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data. EBSCO ebook academic collection. Princeton University Press.
Jain P. (2016). An Introduction to Astronomy and Astrophysics. CRC Press.
Korner-Nievergelt F. et al. (2015). Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan. Elsevier Science.
Kruschke J. (2010). Doing Bayesian Data Analysis: A Tutorial Introduction with R. Elsevier Science.
Lunn D., C. Jackson, N. Best, A. Thomas, and D. Spiegelhalter (2012). The BUGS Book: A Practical Introduction to Bayesian Analysis. Chapman & Hall/CRC Texts in Statistical Science. Taylor & Francis.
McElreath R. (2016). Statistical Rethinking: A Bayesian Course with Examples in R and Stan. Chapman & Hall/CRC Texts in Statistical Science. CRC Press.
Muenchen R. A. and J. M. Hilbe (2010). R for Stata Users. Statistics and Computing. Springer.
Pole A., M. West, and J. Harrison (1994). Applied Bayesian Forecasting and Time Series Analysis. Springer.
R Development Core Team (2008). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. Vienna.
Smithson M. and E. C. Merkle (2013). Generalized Linear Models for Categorical and Continuous Limited Dependent Variables. Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences. Taylor & Francis.
Suess E. A. and B. E. Trumbo (2010). Introduction to Probability Simulation and Gibbs Sampling with R. Use R! Series. Springer.
Team Stan (2016). Stan Modeling Language Users Guide and Reference Manual, Version 2.14.0.
Teetor P. (2011). R Cookbook. O'Reilly Media.
Weisberg H. (2014). Willful Ignorance: The Mismeasure of Uncertainty. Wiley.
Zuur A. F., J. M. Hilbe, and E. N. Ieno (2013). A Beginner's Guide to GLM and GLMM with R: A Frequentist and Bayesian Perspective for Ecologists. Highland Statistics.
Abazajian K. N. et al. (2009). “The seventh data release of the Sloan Digital Sky Survey.” Astrophys. J. Suppl. 182, 543–558. DOI: 10.1088/0067-0049/182/2/543. arXiv:0812.0649.
Aeschbacher S. et al. (2012). “A novel approach for choosing summary statistics in approximate Bayesian computation.” Genetics 192(3), 1027–1047. DOI: 10.1534/genetics.112.143164.
Akaike H. (1974). “A new look at the statistical model identification.” IEEE Trans. Automatic Control 19(6), 716–723.
Akeret J. et al. (2015). “Approximate Bayesian computation for forward modeling in cosmology.” J. Cosmology Astroparticle Phys. 8, 043. DOI: 10.1088/1475-7516/2015/08/043. arXiv:1504.07245.
Alam S. et al. (2015). “The eleventh and twelfth data releases of the Sloan Digital Sky Survey: final data from SDSS-III.” Astrophys. J. Suppl. 219, 12. DOI: 10.1088/0067-0049/219/1/12. arXiv: 1501.00963 [astro-ph.IM].
Almeida L. A. et al. (2015). “Discovery of the massive overcontact binary VFTS352: evidence for enhanced internal mixing.” Astrophys. J. 812, 102. DOI: 10.1088/0004-637X/812/2/102. arXiv: 1509.08940[astro-ph.SR].
Andreon S. (2011). “Understanding better (some) astronomical data using Bayesian methods.” ArXiv e-prints. arXiv: 1112.3652 [astro-ph.IM].
Andreon S. and M. A. Hurn (2010). “The scaling relation between richness and mass of galaxy clusters: a Bayesian approach.” Mon. Not. Roy. Astronom. Soc. 404, 1922–1937. DOI: 10.1111/j.1365-2966.2010.16406.x. arXiv: 1001.4639 [astro-ph.CO].
Baldwin J. A. et al. (1981). “Classification parameters for the emission-line spectra of extragalactic objects.” Publ. Astronom. Soc. Pacific 93, 5–19. DOI: 10.1086/130766.
Bamford S. P. et al. (2009). “Galaxy zoo: the dependence of morphology and colour on environment.” Mon. Not. Roy. Astronom. Soc. 393, 1324–1352. DOI: 10.1111/j.1365-2966.2008.14252.x. arXiv: 0805.2612.
Bastian N. et al. (2010). “A universal stellar initial mass function? a critical look at variations.” Ann. Rev. Astron. Astrophys. 48, 339–389. DOI: 10.1146/annurev-astro-082708-101642. arXiv: 1001.2965.
Beaumont M. A. et al. (2009). “Adaptive approximate Bayesian computation.” Biometrika, asp052.
Benson A. J. (2010). “Galaxy formation theory.” Phys. Rep. 495, 33–86. DOI: 10.1016/j.physrep.2010.06.001. arXiv: 1006.5394 [astro-ph.CO].
Betancourt M. (2015). “Continuing sampling.”æ!msg/stan-users/tlIZW78M3zA/ZHUNqR8l5MkJ (visited on 07/04/2016).
Betancourt M. (2016). “Some Bayesian modeling techniques in stan.” (visited on 06/18/2016).
Betoule M. et al. (2014). “Improved cosmological constraints from a joint analysis of the SDSS-II and SNLS supernova samples.” Astron. Astrophys. 568, A22. DOI: 10.1051/0004-6361/201423413. arXiv: 1401.4064.
Bett P. et al. (2007). “The spin and shape of dark matter haloes in the Millennium simulation of a ∧ cold dark matter universe.” Mon. Not. Roy. Astronom. Soc. 376, 215–232. DOI: 10.1111/j.1365-2966.2007.11432.x. eprint: arXiv: astro-ph/0608607.
Biffi V. and U. Maio (2013). “Statistical properties of mass, star formation, chemical content and rotational patterns in early z [greaterorsimilar] 9 structures.” Mon. Not. Roy. Astronom. Soc. 436, 1621–1638. DOI: 10.1093/mnras/stt1678. arXiv: 1309.2283[].
Blanton M. R. et al. (2011). “Improved background subtraction for the Sloan Digital Sky Survey images.” Astronom. J. 142, 31 DOI: 10.1088/ 0004-6256/142/1/31. arXiv: 1105.1960 [astro-ph.IM].
Bleem L. E. et al. (2015). “Galaxy clusters discovered via the Sunyaev–Zel'dovich effect in the 2500-square-degree SPT-SZ survey.” Astrophys. J. Suppl. 216, 27. DOI: 10.1088/0067-0049/216/2/27. arXiv: 1409.0850.
Bonnarel F. et al. (2000). “The ALADIN interactive sky atlas. A reference tool for identification of astronomical sources.” A&AS 143, 33–40. DOI: 10.1051/aas:2000331.
Bradford J. D. et al. (2015). “A study in blue: the baryon content of isolated low-mass galaxies.” Astrophys. J. 809, 146. DOI: 10.1088/0004-637X/809/2/146. arXiv: 1505.04819.
Burkert A. and S. Tremaine (2010). “A correlation between central supermassive black holes and the globular cluster systems of early-type galaxies.” Astrophys. J. 720, 516–521. DOI: 10.1088/0004-637X/720/1/516. arXiv: 1004.0137 [astro-ph.CO].
Burr T. and A. Skurikhin (2013). “Selecting summary statistics in approximate bayesian computation for calibrating stochastic models.” BioMed Res. Int. 2013.
Cameron E. (2011). “On the estimation of confidence intervals for binomial population proportions in astronomy: the simplicity and superiority of the Bayesian approach.” Publ. Astronom. Soc. Australia 28, 128–139. DOI: 10.1071/AS10046. arXiv: 1012.0566 [astro-ph.IM].
Cameron E. and A. N. Pettitt (2012). “Approximate Bayesian computation for astronomical model analysis: a case study in galaxy demographics and morphological transformation at high redshift.” Mon. Not. Roy. Astronom. Soc. 425, 44–65. DOI: 10.1111/j.1365-2966.2012.21371.x. arXiv: 1202.1426 [astro-ph.IM].
Chabrier G. (2003). “Galactic stellar and substellar initial mass function.” Publ. Astronom. Soc. Pacific 115, 763–795. DOI: 10.1086/376392. eprint:arXiv:astro-ph/0304382.
Chattopadhyay G. and S. Chattopadhyay (2012). “Monthly sunspot number time series analysis and its modeling through autoregressive artificial neural network.” Europ. Physical J. Plus 127, 43. DOI: 10.1140/epjp/i2012-12043-9. arXiv: 1204.3991 [physics.gen-ph].
Conley A. et al. (2011). “Supernova constraints and systematic uncertainties from the first three years of the Supernova Legacy Survey.” Astrophys. J. Suppl. 192, 1. DOI: 10.1088/0067-0049/192/1/1. arXiv: 1104.1443[astro-ph.CO].
Consul P. C. and F. Famoye (1992). “Generalized poisson regression model.” Commun. Statistics – Theory Meth. 21(1), 89–109. DOI: 10.1080/03610929208830766.
Cortese L. and T. M. Hughes (2009). “Evolutionary paths to and from the red sequence: star formation and HI properties of transition galaxies at z ∼ 0.” Mon. Not. Roy. Astronom. Soc. 400, 1225–1240. DOI: 10.1111/j.1365-2966.2 009.15548.x. arXiv: 0908.3564.
de Souza R. S. and B. Ciardi (2015). “AMADA–Analysis of multidimensional astronomical datasets.” Astron. Comput. 12, 100–108. DOI: 10.1016/j.ascom. 2015.06.006. arXiv: 1503.07736 [astro-ph.IM].
de Souza R. S. et al. (2013). “Dark matter halo environment for primordial star formation.” Mon. Not. Roy. Astronom. Soc. 428, 2109–2117. DOI: 10.1093/mnras/sts181. arXiv: 1209.0825 [astro-ph.CO].
de Souza R. S. et al. (2014). “Robust PCA and MIC statistics of baryons in early mini-haloes.” Mon. Not. Roy. Astronom. Soc. 440, 240–248. DOI: 10.1093/mnras/stu274. arXiv: 1308.6009[].
de Souza R. S. et al. (2015a). “The overlooked potential of generalized linear models in astronomy – I: Binomial regression.” Astron. Comput. 12, 21–32. ISSN: 2213-1337. DOI: URL:
de Souza R. S. et al. (2015b). “The overlooked potential of generalized linear models in astronomy – III. Bayesian negative binomial regression and globular cluster populations.” Mon. Not. Roy. Astronom. Soc. 453, 1928–1940. DOI: 10.1093/mnras/stv1825. arXiv: 1506.04792 [astro-ph.IM].
de Souza R. S., et al. (2016). “Is the cluster environment quenching the Seyfert activity in elliptical and spiral galaxies?” Mon. Not. Roy. Astronom. Soc. 461, 2115–2125. DOI: 10.1093/mnras/stw1459. arXiv: 1603.06256.
Djorgovski S. and M. Davis (1987). “Fundamental properties of elliptical galaxies.” Astrophys. J. 313, 59–68. DOI: 10.1086/164948.
Eisenstein D. J. et al. (2011). “SDSS-III: massive spectroscopic surveys of the distant universe, the Milky Way, and extra-solar planetary systems.” Astronom. J. 142, 72. DOI: 10.1088/0004-6256/142/3/72. arXiv: 1101.1529 [astro-ph.IM].
Elliott J. et al. (2015). “The overlooked potential of generalized linear models in astronomy – II: Gamma regression and photometric redshifts”. Astron. Comput. 10, 61–72. DOI: 10.1016/j.ascom.2015.01.002. arXiv: 1409.7699 [astro-ph.IM].
Fabian A. C. (2012). “Observational evidence of active galactic nuclei feedback.” Ann. Rev. Astron. Astrophys. 50, 455–489. DOI: 10.1146/annurev-astro-081811-125521. arXiv: 1204.4114.
Famoye F. and K. P. Singh (2006). “Zero-inflated generalized poisson regression model with an application to domestic violence data.” J. Data Sci. 4(1), 117–130. ISSN: 1683-8602.
Feehrer C. E. (2000). “Dances with Wolfs: a short history of sunspot indices.” (visited on 06/18/2016).
Feigelson E. D. and G. J. Babu (1992). “Linear regression in astronomy. II.” Astrophys. J. 397, 55–67. DOI: 10.1086/171766.
Feroz F. and M. P. Hobson (2008). “Multimodal nested sampling: an efficient and robust alternative to Markov Chain Monte Carlo methods for astronomical data analyses.” Mon. Not. Roy. Astronom. Soc. 384, 449–463. DOI: 10.1111/j.1365-2966.2007.12353.x. arXiv: 0704.3704.
Ferrarese L. and D. Merritt (2000). “A fundamental relation between supermassive black holes and their host galaxies.” Astrophys. J. 539, L9–L12. DOI: 10.1086/312838. eprint: astro-ph/0006053.
Fontanot F. (2014). “Variations of the initial mass function in semi-analytical models.” Mon. Not. Roy. Astronom. Soc. 442, 3138–3146. DOI: 10.1093/mnras/stu1078. arXiv: 1405.7699.
Foreman-Mackey D. et al. (2013). “emcee: the MCMC hammer.” Publ. Astronom. Soc. Pacific 125, 306–312. DOI: 10.1086/670067. arXiv: 1202.3665 [astro-ph.IM].
Gebhardt K. et al. (2000). “Black hole mass estimates from reverberation mapping and from spatially resolved kinematics.” Astrophys. J. 543, L5–L8. DOI: 10.1086/318174. eprint: astro-ph/0007123.
Gelfand A. E. and A. F. M. Smith (1990). “Sampling-based approaches to calculating marginal densities.” J. Amer. Statist. Assoc. 85(410), 398–409.
Gelfand A. E. et al. (1990). “Illustration of Bayesian inference in normal data models using Gibbs sampling.” J. Amer. Statist. Assoc. 85(412), 972–985. DOI: 10.1080/01621459.1990.10474968.
Gelman A. (2006). “Prior distributions for variance parameters in hierarchical models.” Bayesian Anal. 1(3), 515–533.
Gelman A. et al. (2014). “Understanding predictive information criteria for Bayesian models.” Statist. Comput. 24(6), 997–1016. DOI: 10.1007/s11222-013-9416-2.
Gelman A. et al. (2015). “Stan: a probabilistic programming language for bayesian inference and optimization.” J. Educational and Behavioral Statist. DOI: 10.3102/1076998615606113. eprint:
Geman S. and D. Geman (1984). “Stochastic relaxation, Gibbs distribution, and the Bayesian restoration of images.” IEEE Trans. Pattern Recognition 6, 721–741.
Graczyk D. et al. (2011). “The optical gravitational lensing experiment. The OGLE-III catalog of variable stars. XII. Eclipsing binary stars in the large magellanic cloud.” Acta Astron. 61, 103–122. arXiv: 1108.0446 [astro-ph.SR].
Guy J. et al. (2007). “SALT2: using distant supernovae to improve the use of type Ia supernovae as distance indicators.” Astron. Astrophys. 466, 11–21. DOI: 10.1051/0004-6361:20066930. eprint: astro-ph/0701828.
Hadin J. W. (2012). “Modeling underdispersed count data with generalized Poisson regression.” Stata J. 12(4), 736–747.
Hahn O. et al. (2007). “Properties of dark matter haloes in clusters, filaments, sheets and voids.” Mon. Not. Roy. Astronom. Soc. 375, 489–499. DOI: 10.1111/j.1365-2966.2006.11318.x. eprint: arXiv: astro-ph/0610280.
Harris G. L. H. and W. E. Harris (2011). “The globular cluster/central black hole connection in galaxies.” Mon. Not. Roy. Astronom. Soc. 410, 2347–2352. DOI: 10.1111/j.1365-2966.2010.17606.x. arXiv: 1008.4748 [astro-ph.CO].
Harris W. E. et al. (2013). “A catalog of globular cluster systems: what determines the size of a galaxy's globular cluster population?” Astrophys. J. 772, 82. DOI: 10.1088/0004-637X/772/2/82. arXiv: 1306.2247[astro-ph.GA].
Harris G. L. H. et al. (2014). “Globular clusters and supermassive black holes in galaxies: further analysis and a larger sample.” Mon. Not. Roy. Astronom. Soc. 438, 2117–2130. DOI: 10.1093/mnras/stt2337. arXiv: 1312.5187[astro-ph.GA].
Hastings W. K. (1970). “Monte Carlo sampling methods using Markov chains and their applications.” Biometrika 57, 97–109. DOI: 10.1093/biomet/57.1.97.
Hathaway D. H. (2015). “The solar cycle.” Living Rev. Solar Phy. 12. DOI: 10.1007/lrsp-2015-4. arXiv: 1502.07020 [astro-ph.SR].
Hilbe J. M. and W. H. Greene (2007). Count response regression models, in Epidemiology and Medical Statistics, eds. C. R. Rao, J. P. Miller, and D. C. Rao, Elsevier Handbook of Statistics Series.
Hilbe J. M. (2016). “Astrostatistics as new statistical discipline - a historical perspective.” (visited on 06/16/2016).
Hillebrandt W. and J. C. Niemeyer (2000). “Type Ia supernova explosion models.” Ann. Rev. Astron. Astrophys. 38(1), 191–230. DOI: 10.1146/annurev.astro.38.1.191. eprint:
Ishida E. E. O. and R. S. de Souza (2013). “Kernel PCA for type Ia supernovae photometric classification.” Mon. Not. Roy. Astronom. Soc. 430, 509–532. DOI: 10.1093/mnras/sts650. arXiv: 1201.6676.
Ishida E. E. O. et al. (2015). “COSMOABC: likelihood-free inference via population monte carlo approximate Bayesian computation.” Astron. Comput. 13, 1–11. DOI: 10.1016/j.ascom.2015.09.001. arXiv: 1504.06129.
Isobe T. et al. (1990). “Linear regression in astronomy.” Astrophys. J. 364, 104–113. DOI: 10.1086/169390.
Jang-Condell H. and L. Hernquist (2001). “First structure formation: a simulation of small-scale structure at high redshift.” Astrophys. J. 548(1), 68.
Janson M. et al. (2014). “The AstraLux Multiplicity Survey: extension to late M-dwarfs.” Astrophys. J. 789, 102. DOI: 10.1088/0004-637X/789/2/102. arXiv: 1406.0535 [astro-ph.SR].
Kashyap V. L. et al. (2002). “Flare heating in stellar coronae.” Astrophys. J. 580, 1118–1132. DOI: 10.1086/343869. eprint: astro-ph/0208546.
Kauffmann G. et al. (2003). “The host galaxies of active galactic nuclei.” Mon. Not. Roy. Astronom. Soc. 346, 1055–1077. DOI: 10.1111/j.1365-2966.2003.07154.x. eprint: astro-ph/0304239.
Kelly B. C. (2007). “Some aspects of measurement error in linear regression of astronomical data.” Astrophys. J. 665, 1489–1506. DOI: 10.1086/519947. arXiv: 0705.2774.
Kessler R. et al. (2010). “Results from the Supernova Photometric Classification Challenge.” Publ. Astronom. Soc. Pacific 122, 1415–1431. DOI: 10.1086/657607. arXiv: 1008.1024 [astro-ph.CO].
Kewley L. J. et al. (2001). “Theoretical modeling of starburst galaxies.” Astrophys. J. 556, 121–140. DOI: 10.1086/321545. eprint: astro-ph/0106324.
Killedar M. et al. (2015). “Weighted ABC: a new strategy for cluster strong lensing cosmology with simulations.” arXiv: 1507.05617[astro-ph].
Kravtsov A. V. and S. Borgani (2012). “Formation of galaxy clusters.” Ann. Rev. Astron. Astrophys. 50, 353–409. DOI: 10.1146/annurev-astro-081811-125502. arXiv: 1205.5556 [astro-ph.CO].
Kroupa P. (2001). “On the variation of the initial mass function.” Mon. Not. Roy. Astronom. Soc. 322, 231–246. DOI: 10.1046/j.1365-8711.2001.04022.x. eprint: arXiv: astro-ph/0009005.
Kruijssen J. M. D. (2014). “Globular cluster formation in the context of galaxy formation and evolution.” Classical Quant. Grav. 31(24), 244006. DOI: 10.1088/0264-9381/31/24/244006. arXiv: 1407.2953.
Kuo L. and B. Mallick (1998). “Variable selection for regression models.” Sankhyā: Indian J. Statist., Series B (1960–2002) 60(1), 65–81.
Lansbury G. B. et al. (2014). “Barred S0 galaxies in the Coma cluster.” Mon. Not. Roy. Astronom. Soc. 439(2), 1749–1764.
Lin C.-A. and M. Kilbinger (2015). “A new model to predict weak-lensing peak counts II. Parameter constraint strategies.” arXiv: 1506.01076.
Lintott C. J. et al. (2008). “Galaxy Zoo: morphologies derived from visual inspection of galaxies from the Sloan Digital Sky Survey.” Mon. Not. Roy. Astronom. Soc. 389, 1179–1189. DOI: 10.1111/j.1365-2966.2008.13689.x. arXiv: 0804.4483.
Lynden-Bell D. (1969). “Galactic nuclei as collapsed old quasars.” Nature 223, 690–694. DOI: 10.1038/223690a0.
Ma C. et al. (2016). “Application of Bayesian graphs to SN Ia data analysis and compression.” Mon. Not. Roy. Atronom. Soc. (preprint). arXiv: 1603.08519.
Macciò A. V. et al. (2007). “Concentration, spin and shape of dark matter haloes: scatter and the dependence on mass and environment.” Mon. Not. Roy. Astronom. Soc. 378, 55–71. DOI: 10.1111/j.1365-2966.2007.11720.x. eprint: arXiv: astro-ph/0608157.
Machida M. N. et al. (2008). “Formation scenario for wide and close binary systems.” Astrophys. J. 677, 327–347. DOI: 10.1086/529133. arXiv: 0709.2739.
Mahajan S. and S. Raychaudhury (2009). “Red star forming and blue passive galaxies in clusters.” Mon. Not. Roy. Astronom. Soc. 400, 687–698. DOI: 10.1111/j.1365-2966.2009.15512.x. arXiv: 0908.2434.
Maio U. et al. (2010). “The transition from population III to population II-I star formation.” Mon. Not. Roy. Astronom. Soc. 407, 1003–1015. DOI: 10.1111/j.1365-2966.2010.17003.x. arXiv: 1003.4992 [astro-ph.CO].
Maio U. et al. (2011). “The interplay between chemical and mechanical feedback from the first generation of stars.” Mon. Not. Roy. Astronom. Soc. 414, 1145–1157. DOI: 10.1111/j.1365- 2966.2011.18455.x. arXiv: 1011.3999[astro-ph.CO].
Mandel K. S. et al. (2011). “Type Ia supernova light curve inference: hierarchical models in the optical and near-infrared.” Astrophys. J. 731, 120. DOI: 10.1088/0004-637X/731/2/120. arXiv: 1011.5910.
Maoz D. et al. (2014). “Observational clues to the progenitors of type Ia supernovae.” Ann. Rev. Astron. Astrophys. 52(1), 107–170. DOI: 10.1146/annurev-astro-082812-141031.
Marley J. and M. Wand (2010). “Non-standard semiparametric regression via BRugs.” J. Statist. Software 37(1), 1–30. DOI: 10.18637/jss.v037.i05.
Masters K. L. et al. (2010). “Galaxy Zoo: passive red spirals.” Mon. Not. Roy. Astronom. Soc. 405, 783–799. DOI: 10.1111/j.1365-2966.2010.16503.x. arXiv: 0910.4113.
McCullagh P. (2002). “What is a statistical model?” Ann. Statist. 30(5), 1225–1310. DOI: 10.1214/aos/1035844977.
Merritt D. (2000). “Black holes and galaxy evolution.” Dynamics of Galaxies: from the Early Universe to the Present, eds. F. Combes, G. A. Mamon, and V. Charmandaris Vol. 197. Astronomical Society of the Pacific Conference Series, p. 221. eprint: astro-ph/9910546.
Merritt D. and L. Ferrarese (2001). “Black hole demographics from the M–σ relation.” Mon. Not. Roy. Astronom. Soc. 320, L30–L34. DOI: 10.1046/j.1365-8711.2001.04165.x. eprint: astro-ph/0009076.
Metropolis N. and S. Ulam (1949). “The Monte Carlo method.” J. Amer. Statist. Assoc. 44(247), 335–341.
Metropolis N. et al. (1953). “Equation of state calculations by fast computing machines.” J. Chem. Phys. 21, 1087–1092.
Mignoli M. et al. (2009). “The zCOSMOS redshift survey: the three-dimensional classification cube and bimodality in galaxy physical properties.” Astron. Astrophys. 493, 39–49. DOI: 10.1051/0004-6361:200810520. arXiv: 0810.2245.
Nelder J. A. and R. W. M. Wedderburn (1972). “Generalized linear models.” J. Royal Statist. Soc., Series A 135, 370–384.
O'Hara R. B. and D. J. Kotze (2010). “Do not log-transform count data.” Meth. Ecology Evol. 1(2), 118–122. DOI: 10.1111/j.2041-210X.2010.00021.x.
O'Hara R. B. and M. J. Sillanpää (2009). “A review of Bayesian variable selection methods: what, how and which.” Bayesian Anal. 4(1), 85–117. DOI: 10.1214/09-ba403.
Oliveira J. M. et al. (2005). “Circumstellar discs around solar mass stars in NGC 6611.” Mon. Not. Roy. Astronom. Soc. 358, L21–L24. DOI: 10.1111/j.1745-3933.2005.00020.x. eprint: astro-ph/0501208.
Orban de Xivry G. et al. (2011). “The role of secular evolution in the black hole growth of narrow-line Seyfert 1 galaxies.” Mon. Not. Roy. Astronom. Soc. 417, 2721–2736. DOI: 10.1111/j.1365-2966.2011.19439.x. arXiv: 1104.5023.
Park T. and G. Casella (2008). “The Bayesian lasso.” J. Amer. Statist. Assoc. 103(482), 681–686. DOI: 10.1198/016214508000000337.
Pawlak M. (2016). “Period–luminosity–colour relation for early-type contact binaries.” Mon. Not. Roy. Astronom. Soc. DOI: 10.1093/mnras/stw269. arXiv: 1602.01467 [astro-ph.SR].
Penna-Lima M. et al. (2014). “Biases on cosmological parameter estimators from galaxy cluster number counts.” J. Cosmol. Astroparticle Phys. 5, 039. DOI: 10.1088/1475-7516/2014/05/039. arXiv: 1312.4430.
Perlmutter S. et al. (1999) “Measurements of and from 42 high-redshift supernovae.” Astrophys. J. 517, 565–586. DOI: 10.1086/307221. eprint: astro-ph/9812133.
Peterson B. M. (2008). “The central black hole and relationships with the host galaxy.” New Astron. Rev. 52, 240–252. DOI: 10.1016/j.newar.2008.06.005.
Pimbblet K. A. et al. (2013). “The drivers of AGN activity in galaxy clusters: AGN fraction as a function of mass and environment.” Mon. Not. Roy. Astronom. Soc. 429, 1827–1839. DOI: 10.1093/mnras/sts470. arXiv: 1212.0261.
Raichoor A. and S. Andreon (2014). “Do cluster properties affect the quenching rate?” Astron. Astorphys. 570, A123. DOI: 10.1051/0004-6361/201424050. arXiv: 1409.4416.
Rhode K. L. (2012). “Exploring the correlations between globular cluster populations and supermassive black holes in giant galaxies.” Astronom. J. 144, 154. DOI: 10.1088/0004-6256/144/5/154. arXiv: 1210.4570 [astro-ph.CO].
Richardson S. and W. R. Gilks (1993). “A Bayesian approach to measurement error problems in epidemiology using conditional independence models.” Amer. J. Epidemiology 138(6), 430–442. eprint:
Riess A. G. et al. (1998). “Observational evidence from supernovae for an accelerating universe and a cosmological constant.” Astronom. J. 116, 1009–1038. DOI: 10.1086/300499. eprint: astro-ph/9805201.
Robin A. C. et al. (2014). “Constraining the thick disc formation scenario of the Milky Way.” Astron. Astrophys. 5691. arXiv: 1406.5384.
Rubin D. B. (1984). “Bayesianly justifiable and relevant frequency calculations for the applied statistician.” Ann. Statist. 12(4), 1151–1172.
Rubin D. et al. (2015). “UNITY: Confronting supernova cosmology's statistical and systematic uncertainties in a unified Bayesian framework.” Astrophys. J. 813, 137. DOI: 10.1088/0004-637X/813/2/137. arXiv: 1507.01602.
Rucinski S. M. (2004). “Contact binary stars of theW UMa-type as distance tracers.” New Astron. Rev. 48, 703–709. DOI: 10.1016/j.newar.2004.03.005. eprint: astro-ph/0311085.
Rue H. et al. (2009). “Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations.” J. Royal Statist. Soc. Series B 71(2), 319–392. DOI: 10.1111/j.1467-9868.2008.00700.x.
Sako M. et al. (2014). “The data release of the Sloan Digital Sky Survey – II Supernova Survey.” arXiv: 1401.3317 [astro-ph.CO].
Salpeter E. E. (1955). “The luminosity function and stellar evolution.” Astrophys. J. 121, 161. DOI: 10.1086/145971.
Sana H. et al. (2012). “Binary interaction dominates the evolution of massive stars.” Science 337, 444. DOI: 10.1126/science.1223344. arXiv: 1207.6397 [astro-ph.SR].
Schafer C. M. and P. E. Freeman (2012). “Likelihood-free inference in cosmology: potential for the estimation of luminosity.” Statistical Challenges in Modern Astronomy V, eds. E. D. Feigelson and B. G. Jogesh, pp. 3–19. Springer.
Schawinski K. et al. (2007). “Observational evidence for AGN feedback in early-type galaxies.” Mon. Not. Roy. Astronom. Soc. 382, 1415–1431. DOI: 10.1111/j.1365-2966.2007.12487.x. arXiv: 0709.3015.
Schwarz G. (1978). “Estimating the dimension of a model.” Ann. Statist. 6(2), 461–464.
Shariff H. et al. (2015). “BAHAMAS: new SNIa analysis reveals inconsistencies with standard cosmology.” arXiv: 1510.05954.
Shimizu T. T. and R. F. Mushotzky (2013). “The first hard X-ray power spectral density functions of active galactic nucleus.” Astrophys. J. 770, 60. DOI: 10.1088/0004-637X/770/1/60. arXiv: 1304.7002 [astro-ph.HE].
Snyder G. F. et al. (2011). “Relation between globular clusters and supermassive black holes in ellipticals as a manifestation of the black hole fundamental plane.” Astrophys.J. 728, L24. DOI: 10.1088/2041-8205/728/1/L24. arXiv: 1101.1299 [astro-ph.CO].
Somerville R. S. et al. (2008). “A semi-analytic model for the co-evolution of galaxies, black holes and active galactic nuclei.” Mon. Not. Roy. Astronom. Soc. 391, 481–506. DOI: 10.1111/j.1365-2966.2008.13805.x. arXiv: 0808.1227.
Spiegelhalter D. J. et al. (2002). “Bayesian measures of model complexity and fit.” J. Royal Statist. Soc., Series B 64(4), 583–639. DOI: 10.1111/1467-9868.00353.
Stan (2016). “Prior choice recommendations.” (visited on 06/27/2016).
Sunyaev R. A. and Y. B. Zeldovich (1972). “The observations of relic radiation as a test of the nature of X-ray radiation from the clusters of galaxies.” Comm. Astrophys. Space Phys. 4, 173.
Tanner M. A. and W. H. Wong (1987). “The calculation of posterior distributions by data augmentation.” J. Amer. Statist. Assoc. 82, 528–540.
Tibshirani R. (1996). “Regression shrinkage and selection via the lasso.” J. Royal Statist. Soc. Series B 58, 267–288.
Tremaine S. et al. (2002). “The slope of the black hole mass versus velocity dispersion correlation.” Astrophys. J. 574, 740–753. DOI: 10.1086/341002. eprint: astro-ph/0203468.
Uemura M. et al. (2015). “Variable selection for modeling the absolute magnitude at maximum of Type Ia supernovae.” PASJ 67, 55. DOI: 10.1093/pasj/psv031. arXiv: 1504.01470 [astro-ph.SR].
Uttley P. et al. (2002). “Measuring the broad-band power spectra of active galactic nuclei with RXTE.” Mon. Not. Roy. Astronom. Soc. 332, 231–250. DOI: 10.1046/j.1365-8711.2002.05298.x. eprint: astro-ph/0201134.
Vaquero J. M. (2007). “Historical sunspot observations: a review.” Adv. Space Res. 40, 929–941. DOI: 10.1016/j.asr.2007.01.087. eprint: astro-ph/0702068.
Vehtari A. and J. Ojanen (2012). “A survey of Bayesian predictive methods for model assessment, selection and comparison.” Statist. Surv. 6, 142–228. DOI: 10.1214/12-SS102.
Vitenti S. D. P. and M. Penna-Lima (2014). “NumCosmo: numerical cosmology.” ASCL: 1408.013.
Wang H. et al. (2011). “Internal properties and environments of dark matter haloes.” Mon. Not. Roy. Astronom. Soc. 413, 1973–1990. DOI: 10.1111/j.1365-2966.2011.18301.x. arXiv: 1007.0612 [astro-ph.CO].
Weyant A. et al. (2013). “Likelihood-free cosmological inference with Type Ia super-novae: approximate Bayesian computation for a complete treatment of uncertainty.” Astrophys. J. 764, 116. DOI: 10.1088/0004-637X/764/2/116. arXiv: 1206.2563 [astro-ph.CO].
White L. A. (2014). “The rise of astrostatistics.” (visited on 06/16/2016).
Wolf R.C. et al. (2016). “SDSS-II Supernova Survey: an analysis of the largest sample of Type Ia supernovae and correlations with host-galaxy spectral properties.” Astrophys. J. 821, 115. DOI: 10.3847/0004-637X/821/2/115. arXiv: 1602.02674.
Zaninetti L. (2013). “The initial mass function modeled by a left truncated beta distribution.” Astrophys. J. 765, 128. DOI: 10.1088/0004-637X/765/2/128. arXiv: 1303.5597 [astro-ph.SR].
Zuur A. F., J. M. Hilbe, and E. N. Ieno (2013), A Beginner's Guide to GLM and GLMM with R: A frequintist and Bayesian perspective for ecologists, Newburgh, UK: Highlands.


Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 991 *
Loading metrics...

Book summary page views

Total views: 1459 *
Loading metrics...

* Views captured on Cambridge Core between 11th May 2017 - 22nd November 2017. This data will be updated every 24 hours.