September 2014
Intermediate to advanced
236 pages
4h 17m
Japanese
Content preview from Think Bayes ―プログラマのためのベイズ統計入門
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66
■
6
章
決定分析
このモデルを実装するクラス
Player
は、次のようになる。
class Player(object):
def
__
init
__
(self, prices, bids, diffs):
self.pdf_price = thinkbayes.EstimatedPdf(prices)
self.cdf_diff = thinkbayes.MakeCdfFromList(diffs)
mu = 0
sigma = numpy.std(diffs)
self.pdf_error = thinkbayes.GaussianPdf(mu, sigma)
ここで
prices
は、ショーケースの値段の並び、
bids
は推定値の並び、
diffs
は差異
diff
の並びである。念のために、
diff = price - bid
である。
pdf_price
は
KDE
で推測した値段の
PDF
を円滑化したものである。
cdf_diff
は
diff
の累積分布で、図6-2で見たものである。
pdf_error
は誤差分布を特徴付ける
PDF
で
あり、
error = price - guess
である。
diff
の分散を使って、
error
の分散を推定する。この推定は、出場者が出す推測
値が戦略的なことがあるので、完全ではない。例えば、
Player2
は
Player1
が実際の値
段を上回ったと思ったなら、非常に低い値段を出すかもしれない。その場合、
diff
は
error
を反映していない。このようなことが頻発するなら、観察さ
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.