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add revise
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yufree committed Jul 4, 2017
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2 changes: 2 additions & 0 deletions .gitignore
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.Rhistory
.RData
.DS_Store
rsconnect
.gitignore
29 changes: 2 additions & 27 deletions 19-ebayes.Rmd
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Expand Up @@ -83,7 +83,6 @@ $$\frac{a}{b} = \frac{c}{d} = \frac{a+b}{c+d}$$
- 下面用MLB的数据说明，首先提取出球员的击球数据：

```{r MLB}
library(knitr)
library(dplyr)
library(tidyr)
library(Lahman)
Expand Down Expand Up @@ -185,6 +184,7 @@ ggplot(career_eb, aes(average, eb_estimate, color = AB)) +
- 经验贝叶斯会给出一个后验分布，这个分布可以用来求可信区间

```{r ci}
library(broom)
# 给出后验分布
career <- Batting %>%
filter(AB > 0) %>%
Expand Down Expand Up @@ -223,18 +223,6 @@ yankee_1998 <- c("brosisc01", "jeterde01", "knoblch01", "martiti02", "posadjo01"
yankee_1998_career <- career_eb %>%
filter(playerID %in% yankee_1998)
# 展示球员的后验分布
library(broom)
yankee_beta <- yankee_1998_career %>%
inflate(x = seq(.18, .33, .0002)) %>%
ungroup() %>%
mutate(density = dbeta(x, alpha1, beta1))
ggplot(yankee_beta, aes(x, density, color = name)) +
geom_line() +
stat_function(fun = function(x) dbeta(x, alpha0, beta0),
lty = 2, color = "black")
# 提取可信区间
yankee_1998_career <- yankee_1998_career %>%
mutate(low = qbeta(.025, alpha1, beta1),
Expand Down Expand Up @@ -394,20 +382,7 @@ career_eb %>%

- 前面描述的是击球率如何求，如何进行区间估计与多个体的错误率控制，面向的个体或整体，那么如何解决比较问题

- 设想多个球员，我们考虑如何去比较他们击球率

```{r ht}
# 选三个球员
career_eb %>%
filter(name %in% c("Hank Aaron", "Mike Piazza", "Hideki Matsui")) %>%
inflate(x = seq(.26, .33, .00025)) %>%
mutate(density = dbeta(x, alpha1, beta1)) %>%
ggplot(aes(x, density, color = name)) +
geom_line() +
labs(x = "Batting average", color = "")
```

- 如果两个球员击球率的概率密度曲线比较接近，那么即便均值有不同我们也无法进行区分；如果重叠比较少，那么我们有理由认为他们之间的差异显著
- 设想多个球员，我们考虑如何去比较他们击球率。如果两个球员击球率的概率密度曲线比较接近，那么即便均值有不同我们也无法进行区分；如果重叠比较少，那么我们有理由认为他们之间的差异显著

- 贝叶斯视角下如何定量描述这个差异是否显著？

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<meta charset="UTF-8">
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<meta name="author" content="Miao YU">


<meta name="date" content="2017-05-21">
<meta name="date" content="2017-07-04">

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<body>



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<div class="book-summary">
Expand Down Expand Up @@ -1221,8 +1220,9 @@ <h2><span class="header-section-number">7.18</span> 重采样推断</h2>
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<meta charset="UTF-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
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<meta content="text/html; charset=UTF-8" http-equiv="Content-Type">
<meta name="description" content="This is notes from yufree">
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<meta name="date" content="2017-07-04">

<meta name="viewport" content="width=device-width, initial-scale=1">
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<div id="header">
<h1 class="title">Notes</h1>
<h4 class="author"><em>Miao YU</em></h4>
<h4 class="date"><em>2017-05-21</em></h4>
<h4 class="date"><em>2017-07-04</em></h4>
</div>
<div id="e7ac94e8aeb0e6a682e8bfb0" class="section level1 unnumbered">
<h1>笔记概述</h1>
Expand Down Expand Up @@ -768,8 +767,9 @@ <h2>笔记目录（已完成）</h2>
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<meta charset="UTF-8">
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