在R中绘制时间序列标准差：阴影/虚线包裹序列的实现

哈哈，我完全懂你想要的那种效果！刚好之前处理过类似的需求，给你两种实用的方案，都是基于你的zoo时间序列来操作的：

ggplot2处理时间序列可视化非常方便，不管是加虚线还是阴影都很容易：

步骤1：把zoo对象转成数据框 #

ggplot更适配数据框格式，我们可以用下面的代码转换：

library(zoo)
library(ggplot2)

# 假设你的zoo对象叫df
df_df <- data.frame(date = index(df), value = coredata(df))

情况1：添加整体序列的标准差范围 #

如果是想给整个序列的均值加减1倍标准差做范围：

# 计算均值和标准差
mean_val <- mean(df_df$value, na.rm = TRUE)
sd_val <- sd(df_df$value, na.rm = TRUE)
upper_bound <- mean_val + sd_val
lower_bound <- mean_val - sd_val

# 绘图：同时加虚线和阴影（可以二选一）
ggplot(df_df, aes(x = date, y = value)) +
  geom_line(color = "black", linewidth = 1) +  # 原始时间序列
  # 红色虚线标注上下标准差
  geom_hline(yintercept = upper_bound, color = "red", linetype = "dashed") +
  geom_hline(yintercept = lower_bound, color = "red", linetype = "dashed") +
  # 红色半透明阴影填充范围（可选）
  geom_ribbon(aes(ymin = lower_bound, ymax = upper_bound), alpha = 0.2, fill = "red") +
  labs(x = "日期", y = "数值", title = "时间序列 + 整体标准差范围") +
  theme_minimal()

情况2：添加滚动标准差的范围 #

如果是想展示滑动窗口内的标准差（比如7天窗口），用rollapply计算：

# 计算滚动均值和滚动标准差（窗口设为7，可根据需求调整）
df_df$roll_mean <- rollapply(df_df$value, width = 7, FUN = mean, fill = NA, align = "center")
df_df$roll_sd <- rollapply(df_df$value, width = 7, FUN = sd, fill = NA, align = "center")
df_df$roll_upper <- df_df$roll_mean + df_df$roll_sd
df_df$roll_lower <- df_df$roll_mean - df_df$roll_sd

# 绘图
ggplot(df_df, aes(x = date, y = value)) +
  geom_line(color = "black", linewidth = 1) +
  # 滚动标准差的红色虚线
  geom_line(aes(y = roll_upper), color = "red", linetype = "dashed") +
  geom_line(aes(y = roll_lower), color = "red", linetype = "dashed") +
  # 滚动范围的阴影（可选）
  geom_ribbon(aes(ymin = roll_lower, ymax = roll_upper), alpha = 0.2, fill = "red", na.rm = TRUE) +
  labs(x = "日期", y = "数值", title = "时间序列 + 滚动标准差范围") +
  theme_minimal()

如果习惯用基础包，也可以轻松实现：

情况1：整体序列的标准差范围 #

# 先绘制原始时间序列
plot(df, col = "black", lwd = 1, xlab = "日期", ylab = "数值", main = "时间序列 + 整体标准差范围")

# 计算均值和标准差
mean_val <- mean(coredata(df), na.rm = TRUE)
sd_val <- sd(coredata(df), na.rm = TRUE)
upper_bound <- mean_val + sd_val
lower_bound <- mean_val - sd_val

# 添加红色虚线
abline(h = upper_bound, col = "red", lty = 2)
abline(h = lower_bound, col = "red", lty = 2)

# 可选：添加半透明阴影
x_vals <- as.numeric(index(df))  # 把日期转成数值方便polygon处理
y_upper <- rep(upper_bound, length(x_vals))
y_lower <- rep(lower_bound, length(x_vals))
# 绘制阴影（边框设为NA避免多余线条）
polygon(c(x_vals, rev(x_vals)), c(y_upper, rev(y_lower)), col = adjustcolor("red", alpha.f = 0.2), border = NA)
# 把原始线再画一遍，避免被阴影盖住
lines(df, col = "black", lwd = 1)

情况2：滚动标准差的范围 #

# 计算滚动均值和标准差
roll_mean <- rollapply(coredata(df), width = 7, FUN = mean, fill = NA, align = "center")
roll_sd <- rollapply(coredata(df), width = 7, FUN = sd, fill = NA, align = "center")
roll_upper <- roll_mean + roll_sd
roll_lower <- roll_mean - roll_sd

# 转成zoo对象和原序列对齐
roll_upper_zoo <- zoo(roll_upper, index(df))
roll_lower_zoo <- zoo(roll_lower, index(df))

# 绘图
plot(df, col = "black", lwd = 1, xlab = "日期", ylab = "数值", main = "时间序列 + 滚动标准差范围")
# 添加滚动标准差虚线
lines(roll_upper_zoo, col = "red", lty = 2)
lines(roll_lower_zoo, col = "red", lty = 2)

# 可选：添加阴影
x_vals <- as.numeric(index(df))
polygon(c(x_vals, rev(x_vals)), c(coredata(roll_upper_zoo), rev(coredata(roll_lower_zoo))), 
        col = adjustcolor("red", alpha.f = 0.2), border = NA)
# 重新绘制原始线
lines(df, col = "black", lwd = 1)

你可以根据自己的需求选择整体或滚动的版本，虚线和阴影也可以自由组合~

内容的提问来源于stack exchange，提问作者aipam