我正在尝试使用ggplot绘制概率密度图。我的问题是曲线下面积不等于1。建议表示赞赏。
示例图表...生成此图表的代码如下:Y轴看起来像是小型垃圾箱的计数,而不是落入垃圾箱的概率。示例代码here是我在准备此图表时提供的资源之一。
示例代码......其中大部分是数据......代码的关键位在底部......
library(ggplot2)
library(reshape)
library(plyr)
library(scales)
Date <- as.Date(
c("1976-01-16", "1976-02-15", "1976-03-16", "1976-04-15", "1976-05-16",
"1976-06-15", "1976-07-16", "1976-08-16", "1976-09-15", "1976-10-16",
"1976-11-15", "1976-12-16", "1977-01-16", "1977-02-14", "1977-03-16",
"1977-04-15", "1977-05-16", "1977-06-15", "1977-07-16", "1977-08-16",
"1977-09-15", "1977-10-16", "1977-11-15", "1977-12-16", "1978-01-16",
"1978-02-14", "1978-03-16", "1978-04-15", "1978-05-16", "1978-06-15",
"1978-07-16", "1978-08-16", "1978-09-15", "1978-10-16", "1978-11-15",
"1978-12-16", "1979-01-16", "1979-02-14", "1979-03-16", "1979-04-15",
"1979-05-16", "1979-06-15", "1979-07-16", "1979-08-16", "1979-09-15",
"1979-10-16", "1979-11-15", "1979-12-16", "1980-01-16", "1980-02-15",
"1980-03-16", "1980-04-15", "1980-05-16", "1980-06-15", "1980-07-16",
"1980-08-16", "1980-09-15", "1980-10-16", "1980-11-15", "1980-12-16",
"1981-01-16", "1981-02-14", "1981-03-16", "1981-04-15", "1981-05-16",
"1981-06-15", "1981-07-16", "1981-08-16", "1981-09-15", "1981-10-16",
"1981-11-15", "1981-12-16", "1982-01-16", "1982-02-14", "1982-03-16",
"1982-04-15", "1982-05-16", "1982-06-15", "1982-07-16", "1982-08-16",
"1982-09-15", "1982-10-16", "1982-11-15", "1982-12-16", "1983-01-16",
"1983-02-14", "1983-03-16", "1983-04-15", "1983-05-16", "1983-06-15",
"1983-07-16", "1983-08-16", "1983-09-15", "1983-10-16", "1983-11-15",
"1983-12-16", "1984-01-16", "1984-02-15", "1984-03-16", "1984-04-15",
"1984-05-16", "1984-06-15", "1984-07-16", "1984-08-16", "1984-09-15",
"1984-10-16", "1984-11-15", "1984-12-16", "1985-01-16", "1985-02-14",
"1985-03-16", "1985-04-15", "1985-05-16", "1985-06-15", "1985-07-16",
"1985-08-16", "1985-09-15", "1985-10-16", "1985-11-15", "1985-12-16"))
GOLD <- c(
-0.104, 0.051, 0.011, -0.035, -0.008, -0.010, -0.065, -0.067, 0.041, 0.017,
0.126, 0.023, -0.011, 0.029, 0.087, 0.007, -0.016, -0.044, 0.048, -0.013,
0.030, 0.062, -0.029, 0.042, 0.078, 0.028, 0.031, -0.045, 0.005, 0.043,
0.028, 0.090, 0.030, 0.072, -0.094, 0.009, 0.093, 0.080, -0.014, -0.013,
0.077, 0.084, 0.058, 0.021, 0.184, 0.097, 0.002, 0.169, 0.474, -0.014,
-0.168, -0.067, -0.007, 0.169, 0.071, -0.025, 0.077, -0.022, -0.059, -0.044,
-0.063, -0.103, -0.003, -0.008, -0.031, -0.040, -0.113, 0.005, 0.081, -0.014,
-0.057, -0.009, -0.062, -0.026, -0.117, 0.061, -0.046, -0.058, 0.080, 0.076,
0.190, -0.031, -0.019, 0.074, 0.079, 0.022, -0.144, 0.030, 0.013, -0.057,
0.026, -0.017, -0.012, -0.042, -0.030, 0.015, -0.043, 0.041, 0.022, -0.032,
-0.011, 0.001, -0.083, 0.004, -0.019, -0.002, 0.003, -0.065, -0.063, 0.017,
-0.044, 0.134, -0.022, -0.014, -0.008, 0.033, -0.014, 0.017, -0.004, -0.023)
df <- data.frame(Date=Date, GOLD=GOLD)
p <- ggplot(data=df, aes(x=GOLD, y=..density..)) +
stat_density(fill='grey50') +
xlab('Percent change on previous month') +
ylab('Density') +
opts(title='Change in Gold Price in the US')
ggsave(p, width=8, height=4, filename='plot.png', dpi=125)
答案 0 :(得分:7)
我认为这不是ggplot的问题,而是你对密度图中y轴的理解。 R中的基础绘图功能绘制相同的东西。您可以将呼叫设置为y=..scaled..
以获得相对密度,但如果使用stat_bin()
,您将看到实际的直方图,并注意到它不是计数。如果您愿意,可以使用以下内容对数据进行规范化:
GOLD_N <- (GOLD- mean(GOLD))/sd(GOLD)
df <- data.frame(Date=Date, GOLD=GOLD,GOLD_N=GOLD_N)
然后运行你的情节它看起来像这样:
您应该观看此视频,了解如何解释密度函数http://www.youtube.com/watch?v=Fvi9A_tEmXQ但是,如果您习惯于盯着PDF并且总和为1,那么对数据进行标准化将为您提供更直观的绘图。不会误解y轴。 y不是密度中随机绘制的值等于x的概率。