Timeline for Rigorous real analysis book for probability theory?
Current License: CC BY-SA 3.0
10 events
| when toggle format | what | by | license | comment | |
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| May 20, 2017 at 22:02 | vote | accept | Matt Brenneman | ||
| Feb 3, 2017 at 14:58 | comment | added | whuber♦ | @Cardinal ... unless you want to dip into Edward Nelson's Radically Elementary Probability Theory. By using nonstandard analysis, he only needs to deal with finite probability spaces. (All his disclaimers aside, though, that book requires even more mathematical sophistication than a rigorous measure theory text would, IMHO.) | |
| Feb 3, 2017 at 14:23 | history | edited | Andre Silva | CC BY-SA 3.0 |
edited tags as per http://meta.stats.stackexchange.com/questions/4485/understanding-the-use-of-the-education-tag/4486#4486
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| Sep 23, 2014 at 20:53 | answer | added | seanv507 | timeline score: 3 | |
| Sep 23, 2014 at 17:24 | history | made wiki | Post Made Community Wiki by whuber♦ | ||
| Sep 23, 2014 at 17:14 | answer | added | Alecos Papadopoulos | timeline score: 3 | |
| Sep 23, 2014 at 15:29 | comment | added | Matt Brenneman | I am looking for a textbook on mathematical statistics that provides rigorous proofs of results from advanced calculus/real analysis that are not measure theoretic in natures. There a number of elementary results involving variable transformations, mgfs (Laplace transformations) etc that do not involve measure theory. | |
| Sep 23, 2014 at 15:16 | answer | added | EdM | timeline score: 2 | |
| Sep 23, 2014 at 15:09 | comment | added | cardinal | Neither Hogg & Craig nor Casella & Berger are texts on probability theory. Are you asking for texts on mathematical statistics from a rigorous (measure-theoretic) viewpoint? If you don't want any skimping on the proofs, ultimately you'll have to face up to some measure-theoretic ideas. | |
| Sep 23, 2014 at 14:48 | history | asked | Matt Brenneman | CC BY-SA 3.0 |