(Very tiny amendment, to this blog post from October 2015, now put in, July 2018.)
This particular FocuStat Blog Post rather quickly earned itself some extra fame, partly via Steven Pinker's twitter message: "Sophisticated new analysis of the stats of war by Nils Lid Hjort affirms a decline over time, but finds the sharpest in 1965, nor 1945."
He was kind enough to write: "It’s a fascinating and sophisticated analysis, beautifully presented. It is interesting to consider 1965 as a possible breakpoint for a historical decline war. Certainly one finds mainstream attitudes changing around then, with an unprecedented (I think) antiwar movement; I suspect an analysis of cultural motifs (perhaps with Google ngrams) would show a transition starting around then."
Another professor, who contributes regularly to the statistics and analyses of war-and-conflict data, wrote (to a colleague, not to me directly): "Thank you so much for sharing that link. That’s such a good article. Really informative and spectacularly well written (funny, clear, etc.) I really hope he takes it beyond a blog post. There is an important, publishable article in this."
This attention has caused the Blog Post to be re-blogged here and there, etc. We at FocuStat are also seeing a bit of positive spill-over effect, that those reading the War-and-Peace blog then look at some of the others, etc.
Céline Cunens foredrag "Er Game Of Thrones blodigere enn middelalderkriger?", holdt 9. mars 2017 på UiOs Åpen dag, ble filmet, og ligger i NRKs arkiv "Skole", viser det seg:
Godt, klokt og interessant (som allerede meddelt skribenten). Birnbaums teorem fra 1962 er virkelig storveies. Deborah Mayo, som nevnes over, har altså en omfangsrik blog (errorstatistics.com), og der tror jeg Birnbaums fødselsdag, 27. mai, markeres hvert år.
Det er noe galt med "tæggene" over, som ennå ikke springer frem i skyen av tæggede ord? Men det tror jeg ordner seg siden.
1. The FIS didn't follow its own intentions and regulations, for the 23-Feb-2017 Lahti World Championships ski sprint event. Semi-1 skiers had 24:30 minutes, semi-2 skiers only 15:30 minutes, until the finals started. As far as I've understood, FIS has agreed on 20:00 minutes for all, after the work reported on above. As we may see, the semi-1 skiers did best:
A A A B A B (poor Finn Hågen Krogh)
2. Above I wrote: " The solution, from the FIS practical point of view, is to make sure that also the B skiers from the 2nd semifinal have enough recuperation time, even if it takes Justin Bieber or Leiv Ove Andsnes being flown in to keep the zillions of television viewers hooked for a few extra minutes while the athletes breathe. "
I've not yet heard from J. Bieber, but Leiv Ove Andsnes comments (on Facebook):
Leif Ove Andsnes - privat Du verden!
Like · Reply · 1 · 17 mins
Aftenposten holder fortsatt denne saken varm, flere måneder etter at den stod første gang (og der bloggposten over altså ble publisert samtidig). I mars 2016 fortelles det at historien er oversatt til engelsk, kinesisk og farsi.
Cool stuff indeed. I've used your data to fit my gamma process level crossing models, and get sensible answers. Here each person in WoR has a gamma process
Z_0(t) \sim Gamma( a_0 M(t), 1)
governing his or her fate; when Z_0(t) crosses the level
c_0 = \exp(\beta_0 + \beta_1 x_1 + \beta_2 x_2),
he or she dies, and with the threshold determined by (x_1, x_2) = (nobility, gender). Correspondingly, each person in GoT has a gamma process
Z_1(t) \sim Gamma( a_1 M(t), 1)
in his or her rucksack, and death ensues when the process crosses the level
c_1 = \exp(\gamma_0 + \gamma_1 x_1 + \gamma_2 x_2).
This model has two a parameters + three betas (for WoR) + three gammas (for GoT) + one more parameter for the M(t) home function. The point is then to both estimate all parameters and check for significances and differences (I've done so, and will write it up, after checking details with you, Céline). Apparently, belonging to the nobility crowd give you worse chances in WoR, but better survival chances in GoT.
We would also need to invent decent goodness-of-fit tests for these models, incidentally.
This is partly to check out the "comment" function for the FocuStat blog, but also to ask a perhaps simple follow-up question regarding Kristoffer's blog post: How stable are the above results (and associated interpretations) to variations over time? Can important trends be spotted (and interpreted) by using the PCA analysis machinery for Oslo election data 2015, 2013, 2011, 2009, 2007?
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