SlideShare a Scribd company logo
1 of 3
Download to read offline
Bayesian Statistics
Julyan Arbel
julyan.arbel@carloalberto.org
Collegio Carlo Alberto, Moncalieri, Italy
March 17, 2015
Note that The American Statistician, American Scientist and Statistical
Science are rather general audience journals. You can find a brief description
of the journals by following the links below:
The Annals of Probability, The Annals of Statistics, Bayesian Analysis,
Biometrika, Journal of the American Statistical Association, Journal of the
Royal Statistical Society Series B (Statistical Methodology), The American
Statistician, American Scientist, Statistical Science.
References
[1] T. Bayes. An essay towards solving a problem in the doctrine of chances.
Philosophical Transactions (1683-1775), pages 370–418, 1763.
[2] Lorraine Schwartz. On Bayes procedures. Zeitschrift f¨ur Wahrschein-
lichkeitstheorie und verwandte Gebiete, 4(1):10–26, 1965.
[3] W Keith Hastings. Monte Carlo sampling methods using Markov chains
and their applications. Biometrika, 57(1):97–109, 1970.
[4] Dennis V Lindley and Adrian FM Smith. Bayes estimates for the lin-
ear model. Journal of the Royal Statistical Society: Series B (Statistical
Methodology), pages 1–41, 1972.
[5] Thomas S Ferguson. A Bayesian analysis of some nonparametric problems.
The Annals of Statistics, pages 209–230, 1973.
[6] Jose M Bernardo. Reference posterior distributions for Bayesian inference.
Journal of the Royal Statistical Society: Series B (Statistical Methodology),
pages 113–147, 1979.
[7] Persi Diaconis and Donald Ylvisaker. Conjugate priors for exponential
families. The Annals of Statistics, 7(2):269–281, 1979.
[8] Irving J Good. AM Turing’s statistical work in World War II. Biometrika,
pages 393–396, 1979.
1
[9] Persi Diaconis and David Freedman. Finite exchangeable sequences. The
Annals of Probability, pages 745–764, 1980.
[10] Charles M Stein. Estimation of the mean of a multivariate normal distri-
bution. The Annals of Statistics, pages 1135–1151, 1981.
[11] Donald B Rubin. Bayesianly justifiable and relevant frequency calculations
for the applies statistician. The Annals of Statistics, 12(4):1151–1172, 1984.
[12] Persi Diaconis and Donald Ylvisaker. Quantifying prior opinion. Bayesian
Statistics, 2:133–156, 1985.
[13] Persi Diaconis and David Freedman. On the consistency of Bayes estimates.
The Annals of Statistics, pages 1–26, 1986.
[14] Persi Diaconis. Recent progress on de Finetti’s notions of exchangeability.
Bayesian statistics, 3:111–125, 1988.
[15] Robert Tibshirani. Noninformative priors for one parameter of many.
Biometrika, 76(3):604–608, 1989.
[16] Sandy Zabell. RA Fisher on the history of inverse probability. Statistical
Science, pages 247–256, 1989.
[17] Alan E Gelfand and Adrian FM Smith. Sampling-based approaches to cal-
culating marginal densities. Journal of the American statistical Association,
85(410):398–409, 1990.
[18] Eric L Lehmann. Model specification: the views of Fisher and Neyman,
and later developments. Statistical Science, 5(2):160–168, 1990.
[19] Dennis V Lindley. The present position in Bayesian statistics. Statistical
Science, pages 44–65, 1990.
[20] CJ Geyer. Practical Monte Carlo Markov chain (with discussion). Statis-
tical Science, 7(1):473–511, 1992.
[21] William H Jefferys and James O Berger. Ockham’s razor and Bayesian
analysis. American Scientist, pages 64–72, 1992.
[22] Eugene Seneta. Lewis Carroll’s “pillow problems”: on the 1993 centenary.
Statistical science, pages 180–186, 1993.
[23] David Madigan, Jeremy York, and Denis Allard. Bayesian graphical models
for discrete data. International Statistical Review/Revue Internationale de
Statistique, pages 215–232, 1995.
[24] Robert E Kass and Larry Wasserman. The selection of prior distribu-
tions by formal rules. Journal of the American Statistical Association,
91(435):1343–1370, 1996.
2
[25] Felix Abramovich, Theofanis Sapatinas, and Bernard W Silverman.
Wavelet thresholding via a Bayesian approach. Journal of the Royal Sta-
tistical Society: Series B (Statistical Methodology), 60(4):725–749, 1998.
[26] James O Berger. Bayesian analysis: A look at today and thoughts of
tomorrow. Journal of the American Statistical Association, 95(452):1269–
1276, 2000.
[27] L Zhao. Bayesian aspects of some nonparametric problems. The Annals of
Statistics, 28(2):532–552, Jan 2000.
[28] Stephen G Walker and Nils Lid Hjort. On Bayesian consistency. Journal of
the Royal Statistical Society: Series B (Statistical Methodology), 63(4):811–
821, 2001.
[29] Stephen G Walker. New approaches to Bayesian consistency. The Annals
of Statistics, 32(5):2028–2043, 2004.
[30] Bradley Efron. Bayesians, frequentists, and scientists. Journal of the Amer-
ican Statistical Association, 100(469):1–5, 2005.
[31] Roderick J Little. Calibrated Bayes: a Bayes/frequentist roadmap. The
American Statistician, 60(3):213–223, 2006.
[32] G´erard Letac and H´el`ene Massam. Wishart distributions for decomposable
graphs. The Annals of Statistics, 35(3):1278–1323, 2007.
[33] Stephen G Walker, Antonio Lijoi, and Igor Pr¨unster. On rates of conver-
gence for posterior distributions in infinite-dimensional models. The Annals
of Statistics, 35(2):738–746, 2007.
[34] Christian Robert and George Casella. A short history of Markov Chain
Monte Carlo: subjective recollections from incomplete data. Statistical
Science, 26(1):102–115, 2011.
[35] Peter M¨uller and Riten Mitra. Bayesian nonparametric inference–why and
how. Bayesian Analysis, 8(2), 2013.
3

More Related Content

Viewers also liked

Viewers also liked (6)

授業内容
授業内容授業内容
授業内容
 
Arbel oviedo
Arbel oviedoArbel oviedo
Arbel oviedo
 
Causesof effects
Causesof effectsCausesof effects
Causesof effects
 
授業内容
授業内容授業内容
授業内容
 
Lehmann 1990
Lehmann 1990Lehmann 1990
Lehmann 1990
 
Hastings 1970
Hastings 1970Hastings 1970
Hastings 1970
 

Similar to Bayesian Classics

Introduction to Elementary statistics
Introduction to Elementary statisticsIntroduction to Elementary statistics
Introduction to Elementary statisticskrizza joy dela cruz
 
ECO-409-class_one.pptxhrhurutgtututu8yhyyyhyt
ECO-409-class_one.pptxhrhurutgtututu8yhyyyhytECO-409-class_one.pptxhrhurutgtututu8yhyyyhyt
ECO-409-class_one.pptxhrhurutgtututu8yhyyyhytMisterPhilips
 
Steve H. Murdock, David R. Ellis - Applied Demography_ An Introduction to Bas...
Steve H. Murdock, David R. Ellis - Applied Demography_ An Introduction to Bas...Steve H. Murdock, David R. Ellis - Applied Demography_ An Introduction to Bas...
Steve H. Murdock, David R. Ellis - Applied Demography_ An Introduction to Bas...FATIMAHASAN63
 
Inferential statistics
Inferential statisticsInferential statistics
Inferential statisticsSchwayb Javid
 
Table of Contents16304_TTLX_Walker.indd 1 8312 1152.docx
Table of Contents16304_TTLX_Walker.indd   1 8312   1152.docxTable of Contents16304_TTLX_Walker.indd   1 8312   1152.docx
Table of Contents16304_TTLX_Walker.indd 1 8312 1152.docxmattinsonjanel
 
How to do content analysis_abriged
How to do content analysis_abrigedHow to do content analysis_abriged
How to do content analysis_abrigedDevi Prasad
 
Fine Grained Citation Span for References in WIkipedia
Fine Grained Citation Span for References in WIkipediaFine Grained Citation Span for References in WIkipedia
Fine Grained Citation Span for References in WIkipediaBesnik Fetahu
 

Similar to Bayesian Classics (8)

Spss
SpssSpss
Spss
 
Introduction to Elementary statistics
Introduction to Elementary statisticsIntroduction to Elementary statistics
Introduction to Elementary statistics
 
ECO-409-class_one.pptxhrhurutgtututu8yhyyyhyt
ECO-409-class_one.pptxhrhurutgtututu8yhyyyhytECO-409-class_one.pptxhrhurutgtututu8yhyyyhyt
ECO-409-class_one.pptxhrhurutgtututu8yhyyyhyt
 
Steve H. Murdock, David R. Ellis - Applied Demography_ An Introduction to Bas...
Steve H. Murdock, David R. Ellis - Applied Demography_ An Introduction to Bas...Steve H. Murdock, David R. Ellis - Applied Demography_ An Introduction to Bas...
Steve H. Murdock, David R. Ellis - Applied Demography_ An Introduction to Bas...
 
Inferential statistics
Inferential statisticsInferential statistics
Inferential statistics
 
Table of Contents16304_TTLX_Walker.indd 1 8312 1152.docx
Table of Contents16304_TTLX_Walker.indd   1 8312   1152.docxTable of Contents16304_TTLX_Walker.indd   1 8312   1152.docx
Table of Contents16304_TTLX_Walker.indd 1 8312 1152.docx
 
How to do content analysis_abriged
How to do content analysis_abrigedHow to do content analysis_abriged
How to do content analysis_abriged
 
Fine Grained Citation Span for References in WIkipedia
Fine Grained Citation Span for References in WIkipediaFine Grained Citation Span for References in WIkipedia
Fine Grained Citation Span for References in WIkipedia
 

More from Julyan Arbel

Bayesian neural networks increasingly sparsify their units with depth
Bayesian neural networks increasingly sparsify their units with depthBayesian neural networks increasingly sparsify their units with depth
Bayesian neural networks increasingly sparsify their units with depthJulyan Arbel
 
Species sampling models in Bayesian Nonparametrics
Species sampling models in Bayesian NonparametricsSpecies sampling models in Bayesian Nonparametrics
Species sampling models in Bayesian NonparametricsJulyan Arbel
 
Dependent processes in Bayesian Nonparametrics
Dependent processes in Bayesian NonparametricsDependent processes in Bayesian Nonparametrics
Dependent processes in Bayesian NonparametricsJulyan Arbel
 
Asymptotics for discrete random measures
Asymptotics for discrete random measuresAsymptotics for discrete random measures
Asymptotics for discrete random measuresJulyan Arbel
 
Bayesian Nonparametrics, Applications to biology, ecology, and marketing
Bayesian Nonparametrics, Applications to biology, ecology, and marketingBayesian Nonparametrics, Applications to biology, ecology, and marketing
Bayesian Nonparametrics, Applications to biology, ecology, and marketingJulyan Arbel
 
A Gentle Introduction to Bayesian Nonparametrics
A Gentle Introduction to Bayesian NonparametricsA Gentle Introduction to Bayesian Nonparametrics
A Gentle Introduction to Bayesian NonparametricsJulyan Arbel
 
A Gentle Introduction to Bayesian Nonparametrics
A Gentle Introduction to Bayesian NonparametricsA Gentle Introduction to Bayesian Nonparametrics
A Gentle Introduction to Bayesian NonparametricsJulyan Arbel
 
Lindley smith 1972
Lindley smith 1972Lindley smith 1972
Lindley smith 1972Julyan Arbel
 
Diaconis Ylvisaker 1985
Diaconis Ylvisaker 1985Diaconis Ylvisaker 1985
Diaconis Ylvisaker 1985Julyan Arbel
 
Jefferys Berger 1992
Jefferys Berger 1992Jefferys Berger 1992
Jefferys Berger 1992Julyan Arbel
 
Poster DDP (BNP 2011 Veracruz)
Poster DDP (BNP 2011 Veracruz)Poster DDP (BNP 2011 Veracruz)
Poster DDP (BNP 2011 Veracruz)Julyan Arbel
 
Bayesian adaptive optimal estimation using a sieve prior
Bayesian adaptive optimal estimation using a sieve priorBayesian adaptive optimal estimation using a sieve prior
Bayesian adaptive optimal estimation using a sieve priorJulyan Arbel
 

More from Julyan Arbel (17)

UCD_talk_nov_2020
UCD_talk_nov_2020UCD_talk_nov_2020
UCD_talk_nov_2020
 
Bayesian neural networks increasingly sparsify their units with depth
Bayesian neural networks increasingly sparsify their units with depthBayesian neural networks increasingly sparsify their units with depth
Bayesian neural networks increasingly sparsify their units with depth
 
Species sampling models in Bayesian Nonparametrics
Species sampling models in Bayesian NonparametricsSpecies sampling models in Bayesian Nonparametrics
Species sampling models in Bayesian Nonparametrics
 
Dependent processes in Bayesian Nonparametrics
Dependent processes in Bayesian NonparametricsDependent processes in Bayesian Nonparametrics
Dependent processes in Bayesian Nonparametrics
 
Asymptotics for discrete random measures
Asymptotics for discrete random measuresAsymptotics for discrete random measures
Asymptotics for discrete random measures
 
Bayesian Nonparametrics, Applications to biology, ecology, and marketing
Bayesian Nonparametrics, Applications to biology, ecology, and marketingBayesian Nonparametrics, Applications to biology, ecology, and marketing
Bayesian Nonparametrics, Applications to biology, ecology, and marketing
 
A Gentle Introduction to Bayesian Nonparametrics
A Gentle Introduction to Bayesian NonparametricsA Gentle Introduction to Bayesian Nonparametrics
A Gentle Introduction to Bayesian Nonparametrics
 
A Gentle Introduction to Bayesian Nonparametrics
A Gentle Introduction to Bayesian NonparametricsA Gentle Introduction to Bayesian Nonparametrics
A Gentle Introduction to Bayesian Nonparametrics
 
Lindley smith 1972
Lindley smith 1972Lindley smith 1972
Lindley smith 1972
 
Berger 2000
Berger 2000Berger 2000
Berger 2000
 
Seneta 1993
Seneta 1993Seneta 1993
Seneta 1993
 
Diaconis Ylvisaker 1985
Diaconis Ylvisaker 1985Diaconis Ylvisaker 1985
Diaconis Ylvisaker 1985
 
Jefferys Berger 1992
Jefferys Berger 1992Jefferys Berger 1992
Jefferys Berger 1992
 
R in latex
R in latexR in latex
R in latex
 
Poster DDP (BNP 2011 Veracruz)
Poster DDP (BNP 2011 Veracruz)Poster DDP (BNP 2011 Veracruz)
Poster DDP (BNP 2011 Veracruz)
 
Bayesian adaptive optimal estimation using a sieve prior
Bayesian adaptive optimal estimation using a sieve priorBayesian adaptive optimal estimation using a sieve prior
Bayesian adaptive optimal estimation using a sieve prior
 
Seminaire ihp
Seminaire ihpSeminaire ihp
Seminaire ihp
 

Bayesian Classics

  • 1. Bayesian Statistics Julyan Arbel julyan.arbel@carloalberto.org Collegio Carlo Alberto, Moncalieri, Italy March 17, 2015 Note that The American Statistician, American Scientist and Statistical Science are rather general audience journals. You can find a brief description of the journals by following the links below: The Annals of Probability, The Annals of Statistics, Bayesian Analysis, Biometrika, Journal of the American Statistical Association, Journal of the Royal Statistical Society Series B (Statistical Methodology), The American Statistician, American Scientist, Statistical Science. References [1] T. Bayes. An essay towards solving a problem in the doctrine of chances. Philosophical Transactions (1683-1775), pages 370–418, 1763. [2] Lorraine Schwartz. On Bayes procedures. Zeitschrift f¨ur Wahrschein- lichkeitstheorie und verwandte Gebiete, 4(1):10–26, 1965. [3] W Keith Hastings. Monte Carlo sampling methods using Markov chains and their applications. Biometrika, 57(1):97–109, 1970. [4] Dennis V Lindley and Adrian FM Smith. Bayes estimates for the lin- ear model. Journal of the Royal Statistical Society: Series B (Statistical Methodology), pages 1–41, 1972. [5] Thomas S Ferguson. A Bayesian analysis of some nonparametric problems. The Annals of Statistics, pages 209–230, 1973. [6] Jose M Bernardo. Reference posterior distributions for Bayesian inference. Journal of the Royal Statistical Society: Series B (Statistical Methodology), pages 113–147, 1979. [7] Persi Diaconis and Donald Ylvisaker. Conjugate priors for exponential families. The Annals of Statistics, 7(2):269–281, 1979. [8] Irving J Good. AM Turing’s statistical work in World War II. Biometrika, pages 393–396, 1979. 1
  • 2. [9] Persi Diaconis and David Freedman. Finite exchangeable sequences. The Annals of Probability, pages 745–764, 1980. [10] Charles M Stein. Estimation of the mean of a multivariate normal distri- bution. The Annals of Statistics, pages 1135–1151, 1981. [11] Donald B Rubin. Bayesianly justifiable and relevant frequency calculations for the applies statistician. The Annals of Statistics, 12(4):1151–1172, 1984. [12] Persi Diaconis and Donald Ylvisaker. Quantifying prior opinion. Bayesian Statistics, 2:133–156, 1985. [13] Persi Diaconis and David Freedman. On the consistency of Bayes estimates. The Annals of Statistics, pages 1–26, 1986. [14] Persi Diaconis. Recent progress on de Finetti’s notions of exchangeability. Bayesian statistics, 3:111–125, 1988. [15] Robert Tibshirani. Noninformative priors for one parameter of many. Biometrika, 76(3):604–608, 1989. [16] Sandy Zabell. RA Fisher on the history of inverse probability. Statistical Science, pages 247–256, 1989. [17] Alan E Gelfand and Adrian FM Smith. Sampling-based approaches to cal- culating marginal densities. Journal of the American statistical Association, 85(410):398–409, 1990. [18] Eric L Lehmann. Model specification: the views of Fisher and Neyman, and later developments. Statistical Science, 5(2):160–168, 1990. [19] Dennis V Lindley. The present position in Bayesian statistics. Statistical Science, pages 44–65, 1990. [20] CJ Geyer. Practical Monte Carlo Markov chain (with discussion). Statis- tical Science, 7(1):473–511, 1992. [21] William H Jefferys and James O Berger. Ockham’s razor and Bayesian analysis. American Scientist, pages 64–72, 1992. [22] Eugene Seneta. Lewis Carroll’s “pillow problems”: on the 1993 centenary. Statistical science, pages 180–186, 1993. [23] David Madigan, Jeremy York, and Denis Allard. Bayesian graphical models for discrete data. International Statistical Review/Revue Internationale de Statistique, pages 215–232, 1995. [24] Robert E Kass and Larry Wasserman. The selection of prior distribu- tions by formal rules. Journal of the American Statistical Association, 91(435):1343–1370, 1996. 2
  • 3. [25] Felix Abramovich, Theofanis Sapatinas, and Bernard W Silverman. Wavelet thresholding via a Bayesian approach. Journal of the Royal Sta- tistical Society: Series B (Statistical Methodology), 60(4):725–749, 1998. [26] James O Berger. Bayesian analysis: A look at today and thoughts of tomorrow. Journal of the American Statistical Association, 95(452):1269– 1276, 2000. [27] L Zhao. Bayesian aspects of some nonparametric problems. The Annals of Statistics, 28(2):532–552, Jan 2000. [28] Stephen G Walker and Nils Lid Hjort. On Bayesian consistency. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 63(4):811– 821, 2001. [29] Stephen G Walker. New approaches to Bayesian consistency. The Annals of Statistics, 32(5):2028–2043, 2004. [30] Bradley Efron. Bayesians, frequentists, and scientists. Journal of the Amer- ican Statistical Association, 100(469):1–5, 2005. [31] Roderick J Little. Calibrated Bayes: a Bayes/frequentist roadmap. The American Statistician, 60(3):213–223, 2006. [32] G´erard Letac and H´el`ene Massam. Wishart distributions for decomposable graphs. The Annals of Statistics, 35(3):1278–1323, 2007. [33] Stephen G Walker, Antonio Lijoi, and Igor Pr¨unster. On rates of conver- gence for posterior distributions in infinite-dimensional models. The Annals of Statistics, 35(2):738–746, 2007. [34] Christian Robert and George Casella. A short history of Markov Chain Monte Carlo: subjective recollections from incomplete data. Statistical Science, 26(1):102–115, 2011. [35] Peter M¨uller and Riten Mitra. Bayesian nonparametric inference–why and how. Bayesian Analysis, 8(2), 2013. 3