<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[cassie_note的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/cassie_note</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; cassie_note]]></copyright><item><title><![CDATA[数据的探索性分析及R实现]]></title><link>https://blog.youkuaiyun.com/cassie_note/article/details/80369279</link><guid>https://blog.youkuaiyun.com/cassie_note/article/details/80369279</guid><author>cassie_note</author><pubDate>Tue, 22 May 2018 16:22:59 +0800</pubDate><description><![CDATA[一.读入数据



city=read.csv(&amp;amp;quot;2015city.csv&amp;amp;quot;)



二.描述性统计


样本量、均值、方差、标准差、中位数、最小值、最大值、上百分位数与下百分位数差、百分位数、极差、变异系数、偏度系数、峰度系数


data.outline=function(x)
  ## input ###################
  ## x = a vector #########...]]></description><category></category></item><item><title><![CDATA[我的python笔记[leetcode]]]></title><link>https://blog.youkuaiyun.com/cassie_note/article/details/80387878</link><guid>https://blog.youkuaiyun.com/cassie_note/article/details/80387878</guid><author>cassie_note</author><pubDate>Mon, 21 May 2018 09:12:50 +0800</pubDate><description><![CDATA[[leetcode]找出两数之和为指定的数：



class Solution:
    def twoSum(self,nums, target):
        for i,num in enumerate(nums):
            sub_num=target-num
            if sub_num in nums:
                t_inde...]]></description><category></category></item><item><title><![CDATA[多元正态分布的协方差检验、独立性检验及R实现]]></title><link>https://blog.youkuaiyun.com/cassie_note/article/details/80212572</link><guid>https://blog.youkuaiyun.com/cassie_note/article/details/80212572</guid><author>cassie_note</author><pubDate>Sun, 06 May 2018 11:09:23 +0800</pubDate><description><![CDATA[1.单个ppp元正态总体协方差阵的检验

具体步骤：


作统计假设(1)：H0:∑=Ip,H1:∑≠IpH0:∑=Ip,H1:∑≠IpH_0:\sum =I_p,H_1:\sum \neq I_p
统计量：λ=supθ∈Θ0L(μ,Ip)supθ∈ΘL(μ,∑)=(en)np/2|S|n/2exp[−12tr(S)]λ=supθ∈Θ0L(μ,Ip)supθ∈ΘL(μ,∑)=(en)np/2|S|...]]></description><category></category></item><item><title><![CDATA[多元正态分布的均值向量的检验及R实现]]></title><link>https://blog.youkuaiyun.com/cassie_note/article/details/80210070</link><guid>https://blog.youkuaiyun.com/cassie_note/article/details/80210070</guid><author>cassie_note</author><pubDate>Sat, 05 May 2018 21:59:35 +0800</pubDate><description><![CDATA[ppp维正态总体NP(μ,∑)NP(μ,∑)N_P(\mu,\sum)的均值向量检验，X1,X2,⋯,XnX1,X2,⋯,XnX_1,X_2,\cdots,X_n是来自正态总体的样本：



1.∑∑\sum已知时单个总体均值向量的检验：

具体步骤：


作统计假设：H0:μ=μ0,H1:μ≠μ0H0:μ=μ0,H1:μ≠μ0H_0:\mu=\mu_0,H_1:\mu\neq \mu_0
计算样...]]></description><category></category></item><item><title><![CDATA[多元正态分布及软件实现密度函数图像]]></title><link>https://blog.youkuaiyun.com/cassie_note/article/details/80205812</link><guid>https://blog.youkuaiyun.com/cassie_note/article/details/80205812</guid><author>cassie_note</author><pubDate>Sat, 05 May 2018 14:53:26 +0800</pubDate><description><![CDATA[正态分布密度函数及特征函数总结：1.一元标准正态分布N(0,1)N(0,1)：
密度函数：(2π)−12e−y22(2\pi)^{-\frac{1}{2}}e^{-\frac{y^2}{2}}
特征函数：e−t22e^{-\frac{t^2}{2}}
2.一元正态分布N(μ,σ2)N(\mu,\sigma^2):
密度函数：12π√σe−(y−μ)22σ2\frac{1}{\sqrt{2\pi}\s]]></description><category></category></item></channel></rss>