<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[John_AWZ的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/John_AWZ</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; John_AWZ]]></copyright><item><title><![CDATA[小白读《R语言实战》写的读书笔记（第八章）]]></title><link>https://blog.youkuaiyun.com/John_AWZ/article/details/137269986</link><guid>https://blog.youkuaiyun.com/John_AWZ/article/details/137269986</guid><author>John_AWZ</author><pubDate>Tue, 02 Apr 2024 14:43:03 +0800</pubDate><description><![CDATA[而向前向后逐步回归（stepwise stepwise regression,通常称作逐步回归，以避免听起来太冗长），结合了向前逐步回归和向后逐步回归的方法：变量每次进入一个，但是每一步中，变量都会被重新评估，对模型没有贡献的变量将会被删除；当只有一个预测变量，但同时包含变量的幂（如X²，X³）时，称为多项式回归。#在states的多元回归模型中，我们发现Income和Frost 的回归系数不显著，此时我们可以检验不含这两个变量的模型与包含这两项的模型的预测效果是否一样好（见代码清单8-9）。]]></description><category></category></item><item><title><![CDATA[小白读《R语言实战》写的读书笔记（第七章）]]></title><link>https://blog.youkuaiyun.com/John_AWZ/article/details/136853973</link><guid>https://blog.youkuaiyun.com/John_AWZ/article/details/136853973</guid><author>John_AWZ</author><pubDate>Tue, 19 Mar 2024 20:16:28 +0800</pubDate><description><![CDATA[虽然前面的示例使用的是mystats()函数，但我们也可以使用Hmisc和psych包中的describe()函数或者pastecs包中的stat.desc()函数。#可以使用margin.table()或prop.table()生成边际频数和比例：（这里的边际频数指的是按照行或列分组时的每一组的总频数，John注）#这里可以插入的函数有mean(),sd(),var(),max(),median(),length(),range()和quantile()]]></description><category></category></item><item><title><![CDATA[小白读《R语言实战》写的读书笔记（第六章）]]></title><link>https://blog.youkuaiyun.com/John_AWZ/article/details/136504577</link><guid>https://blog.youkuaiyun.com/John_AWZ/article/details/136504577</guid><author>John_AWZ</author><pubDate>Wed, 06 Mar 2024 14:08:43 +0800</pubDate><description><![CDATA[summarize(n = n(), #n = n，第2个n是state.region中的观察数目，在本例中表示有几个地区，第1个n是将这个结果新建一个名称为n的列。ggplot(plotdata, aes(x = reorder(state.region, mean), y = mean)) + #绘制均值的排序条形图。se = sd(Illiteracy)/sqrt(n)) #计算标准误，sqrt(n)代表根号n，标准误=标准差/根号样本量。]]></description><category></category></item><item><title><![CDATA[小白读《R语言实战》写的读书笔记（第五章）]]></title><link>https://blog.youkuaiyun.com/John_AWZ/article/details/136322893</link><guid>https://blog.youkuaiyun.com/John_AWZ/article/details/136322893</guid><author>John_AWZ</author><pubDate>Tue, 27 Feb 2024 15:02:20 +0800</pubDate><description><![CDATA[sub("\\s""."，"Hello There")返回值为Hello.There。names ]]></description><category></category></item><item><title><![CDATA[小白读《R语言实战》写的读书笔记（第四章）]]></title><link>https://blog.youkuaiyun.com/John_AWZ/article/details/136120198</link><guid>https://blog.youkuaiyun.com/John_AWZ/article/details/136120198</guid><author>John_AWZ</author><pubDate>Thu, 15 Feb 2024 14:07:44 +0800</pubDate><description><![CDATA[scale_x_continuous(breaks = seq(0, 60, 10)) + #更改代表工作年限的x轴的范围从0到60，每个格子为10。scale_y_continuous(breaks = seq(0, 30, 5)) + #更改代表薪资的y轴的范围从0到30，每个格子为5。geom_smooth() #拟合曲线  ##选项有：method, formula, color, fill, linetype, size。]]></description><category></category></item><item><title><![CDATA[小白读《R语言实战》写的读书笔记（第三章）]]></title><link>https://blog.youkuaiyun.com/John_AWZ/article/details/136120188</link><guid>https://blog.youkuaiyun.com/John_AWZ/article/details/136120188</guid><author>John_AWZ</author><pubDate>Thu, 15 Feb 2024 14:06:07 +0800</pubDate><description><![CDATA[含义 <- c("数字表示日期（0-31）", "缩写的星期名", "非缩写的星期名", "月份（01-12）", "缩写的月份", "非缩写的月份", "两位数的年份", "四位数的年份")示例 <- c("01-31", "Mon", "Monday", "00-12", "Jan", "January", "07", "2007")符号 <- c("%d", "%a", "%A", "%m", "%b", "%B", "%y", "%Y")]]></description><category></category></item><item><title><![CDATA[小白读《R语言实战》写的读书笔记（第二章）]]></title><link>https://blog.youkuaiyun.com/John_AWZ/article/details/136120178</link><guid>https://blog.youkuaiyun.com/John_AWZ/article/details/136120178</guid><author>John_AWZ</author><pubDate>Thu, 15 Feb 2024 14:04:07 +0800</pubDate><description><![CDATA[比如说，colClasses=c("numeric"，"numeric"，"character"，"NULL"，“numeric"）把前两列读取为数值型变量，把第三列读取为字符型向量，跳过第四列，把第五列读取为数值型向量。#vector是数组中的数据，dimensions是一个数值型的向量，给出了各维度的最大值，dimnames是可选的、各维度名称标签列表。y ]]></description><category></category></item><item><title><![CDATA[小白读《R语言实战》写的读书笔记（第一章）]]></title><link>https://blog.youkuaiyun.com/John_AWZ/article/details/136120163</link><guid>https://blog.youkuaiyun.com/John_AWZ/article/details/136120163</guid><author>John_AWZ</author><pubDate>Thu, 15 Feb 2024 14:02:19 +0800</pubDate><description><![CDATA[sink()函数只用于文本输出，示例：sink(file = NULL, append = FALSE, type = c("output", "message"),split = FALSE)apropos("foo", mode="function") #列出名称中含有foo的所有可用函数。save.image("myfile") #保存工作空间到文件myfile中（默认值为.Rdata)help.search("foo") #以foo为关键词搜索本地帮助文档，或表达式为？]]></description><category></category></item></channel></rss>