1

我已经多次运行下面的脚本并且它一直工作到今天早上，当它突然产生错误消息时：

（terms.formula(formula, data = data) 中的错误：'data' 参数类型错误。

我没有改变任何东西，我需要找出为什么它突然似乎不起作用。以前对类似问题的回答没有帮助。

我的数据：

DPUT(harvest2)
structure(list(Year = c(1971, 1972, 1973, 1974, 1975, 1976, 1977, 
1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 
1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 
2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 
2011, 2012, 2013, 2014, 2015, 2016), Count = c(750, 757, 592, 
693, 667, 757, 719, 670, 733, 796, 923, 921, 944, 1010, 825, 
762, 825, 844, 809, 830, 768, 823, 749, 675, 700, 637, 708, 697, 
754, 694, 636, 717, 786, 731, 769, 732, 710, 610.5, 593, 529, 
664, 788, 731, 644, 653, 656), SexRat = c(1.91812865497076, 2.34567901234568, 
1.69178082191781, 1.46766169154229, 1.30396475770925,     
1.4364406779661, 1.32098765432099, 1.48584905660377, 1.5906976744186, 
1.91414141414141, 1.48905109489051, 1.61382113821138, 1.52380952380952, 
1.87777777777778, 1.75438596491228, 1.6695652173913, 1.81566820276498, 
1.79295154185022, 1.85024154589372, 1.75446428571429, 1.83163265306122, 
1.92857142857143, 1.76635514018692, 1.5, 2.26190476190476,     1.76704545454545,
2.38125, 1.80924855491329, 2.33333333333333, 1.81182795698925, 
2.20446096654275, 2.02790697674419, 2.1140350877193, 2.05, 2.20183486238532, 
1.90983606557377, 2.02262443438914, 1.75116279069767, 1.86842105263158, 
1.87951807228916, 2.08542713567839, 2.01724137931034, 1.95833333333333, 
1.81165919282511, 2.12135922330097, 1.97260273972603)), class = "data.frame", 
row.names = c(NA, -46L))

我的脚本：

# Function for the equation

lm_eqn = function(df){
  m = lm(y ~ poly(x, 3), df) #3rd degree polynomial
  eq <- substitute(italic(y) == a + b %.% italic(x)*","~~italic(r)^2~"="~r2,
                   list(a = format(coef(m)[1], digits = 2),
                        b = format(coef(m)[2], digits = 2),
                        r2 = format(summary(m)$r.squared, digits = 4)))

  as.character(as.expression(eq))
}

# Make the plot

library(ggplot2)
ggplot(harvest2, aes(x = Year, y = Count)) +  
  scale_y_continuous(minor_breaks = seq(500, 1100, by = 50), 
                     breaks = seq(500, 1100, by = 100),
                     limits = c(500, 1100), expand = c(0, 0)) +  
  scale_x_continuous(minor_breaks = seq(1970, 2018, by = 1), 
                     breaks = seq(1970, 2018, by = 5), limits = c(1970, 2018)) +
  geom_point(stat = 'identity', size=2) +
  stat_smooth(method = "lm", se = TRUE, fill = NA, size = 1.3,
              formula = y ~ poly(x, 3, raw = TRUE), col = "red") +
  annotate("text", x = 1975, y = 1075, label = lm_eqn(df), 
           hjust = 0, size = 3.5, parse = TRUE) +
  xlab(" ") + 
  ylab("Count") +
  theme_light() +
  ggtitle(" ")

非常感谢任何帮助。

4

2 回答 2

2

stat_poly_eq从ggpmisc包装中使用怎么样？如果您想将方程和 R2 分成两行，请参阅此内容。

library(ggplot2)
library(ggpmisc)

# define formula
formula1 <- y ~ poly(x, 3, raw = TRUE)

ggplot(harvest2, aes(x = Year, y = Count)) +
  scale_y_continuous(
    minor_breaks = seq(500, 1100, by = 50), breaks = seq(500, 1100, by = 100),
    limits = c(500, 1100), expand = c(0, 0)) +
  scale_x_continuous(
    minor_breaks = seq(1970, 2018, by = 1), breaks = seq(1970, 2018, by = 5),
    limits = c(1970, 2018)) +
  geom_point(stat = "identity", size = 2) +
  stat_smooth(
    method = "lm", se = TRUE, fill = NA, size = 1.3,
    formula = formula1, col = "red") +
  # show the equation and R2
  stat_poly_eq(aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~~")),
    label.x.npc = "left", label.y.npc = "top",
    formula = formula1, parse = TRUE, size = 5) +
  xlab(" ") + ylab("Count") +
  theme_light() +
  ggtitle(" ")

由reprex 包（v0.2.1.9000）于 2019 年 2 月 12 日创建

于 2019-02-13T00:49:27.233 回答
1

@Tung 的回答解决了这个问题，Tung 的评论暗示了原始代码中的错误。我在下面对此进行扩展。

很可能问题出df在以下语句中的使用中：

annotate("text", x = 1975, y = 1075, label = lm_eqn(df), hjust = 0, size = 3.5, parse = TRUE)

df是参数的名称而不是所需的参数，这应该是方程匹配绘制的曲线与传递给相同的数据ggplot：

annotate("text", x = 1975, y = 1075, label = lm_eqn(df = harvest2), hjust = 0, size = 3.5, parse = TRUE)

df误差和可能的错误方程系数/R^2 值将根据搜索路径中是否存在命名变量以及其中存储的对象而有所不同。

@Tung 的代码通过仅定义一次模型公式并将其存储在变量中以及仅将数据作为参数传递一次来确保方程和绘制的曲线之间没有不匹配。

于 2019-09-18T21:35:34.540 回答