August 2015
Intermediate to advanced
272 pages
5h 46m
Japanese
Content preview from Think Stats 第2版 ―プログラマのための統計入門
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80
6 章 確率密度関数
>>> pmf = pdf.MakePmf()
デフォルトでは、結果の
Pmf
は、
mu-3*sigma
から
mu+3*sigma
まで均等にばらま
かれた
101
個の点を含みます。
MakePmf
と
Render
は、
low
,
high
,
n
というキーワード
引数をオプションとして取ることができます。
6.2
カーネル密度推定
カーネル密度推定（
Kernel density estimation
、
KDE
）は、標本を入力として、
データに合致する近似的な円滑
PDF
を求めるアルゴリズムです。詳細は、
http://
ja.wikipedia.org/wiki/
カーネル密度推定
†
で読めます。
scipy
は
KDE
の実装を提供し、
thinkstats2
はその
KDE
を使う
EstimatedPdf
ク
ラスを提供します。
class EstimatedPdf(Pdf):
def __init__(self, sample):
self.kde = scipy.stats.gaussian_kde(sample)
def Density(self, x):
return self.kde.evaluate(x)
__init__
は標本を取って、カーネル密度推定を計算します。結果は
evaluate
メソッ
ドを提供する
gaussian_kde
オブジェクトです。
Density
は値かシーケンスを取り、
gaussian_kde.evaluate
を呼び出し、結果とし
て密度を返します。名前に「
Gaussian
」という語が含まれるのは、 ...
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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.