R 如何用ggplot2绘制三差非线性回归

我试图用ggplot2绘制三种不同的非线性回归（就像我在下面的graphpad（虚线）中所做的那样）（因为graphpad无法比较各组之间的非线性回归）：

到目前为止，我画了这个图表：

使用以下代码：

gp <- ggplot(datapoidsmono, aes(x = time, y = weight)) +
  stat_summary(aes(color = group), fun.data="mean_sdl", fun.args = list(mult=1), geom="errorbar", position = "identity", size=0.5, width=0.2) +
  stat_summary(fun.y = "mean", geom = "point", size=3, aes(shape=group,color=group)) + 
  scale_x_discrete(name = "Days after injection") +
  scale_y_continuous(name = "Weight (g)", limits=c(0, 4000), breaks = seq(0, 4000,500)) +
  scale_color_manual(values=c("green", "blue", "red"), name="Treatment", labels=c("A","B","C")) +
  scale_shape_manual(values=c(15,16,17), name  ="Treatment", labels=c("A", "B", "C")) +
  ggtitle("Weight variation over time") + theme(plot.title = element_text(hjust = 0.5)) +
  theme(legend.position = "right") + 
  theme(legend.background = element_rect(size=0.5, linetype="solid", color ="black", fill="white")) +
  theme(axis.line.x = element_line(size = 0.5, color = "black"),axis.text.x = element_text(color="black", size = 12),axis.line.y = element_line(size = 0.5, color = "black"),axis.text.y = element_text(color="black", size = 12),axis.title = element_text(size =15, face="bold"),plot.title = element_text(size =20, face = "bold"),panel.grid.major = element_line(color = "#F1F1F1"),panel.grid.minor = element_blank(), panel.background = element_blank())

这个也没有（）：

任何想法或线索都有助于继续！谢谢

---

更新 正如@PoGibas所建议的，我在aes中的第一行中添加了“group=group”，这条线画得很好

我尝试了Multiple解决方案以获得完美贴合：

gp + ggplot(aes(group=group))
  stat_smooth(method = "lm", formula = y ~ x, size = 1, se = FALSE,colour = "black") + 
  stat_smooth(method = "lm", formula = y ~ x + I(x^2),size = 1, se = FALSE, colour = "blue") + 
  stat_smooth(method = "loess", formula = y ~ x, size = 1, se = FALSE, colour = "red") + 
  stat_smooth(method = "gam", formula = y ~ s(x), size = 1, se = FALSE, colour = "green") + 
  stat_smooth(method = "gam", formula = y ~ s(x, k = 3), size = 1, se = FALSE, colour = "violet") +
  stat_smooth(method = "auto", se=F, colour = "yellow")

但我认为简单地

gp+stat\u smooth（）

就可以完美地完成这项工作（使用了黄土方法）

现在，我正试图改变外观（虚线）和适合的颜色

我尝试了

gp+stat\u平滑（se=F，aes（fill=group））

但是现在我有了另一个图例框，我的线条总是用相同的颜色

我还尝试在aes中添加

linetype=group

，但当我使用

scale\u linetype\u手册（值=c（“虚线”、“虚线”、“虚线”）

时，每一行都是虚线（包括错误条）

完整的代码是：

ggplot(datapoidsmono, aes(x = time, y = weight, group=group, linetype=group)) +
  stat_summary(aes(color = group), fun.data="mean_sdl", fun.args = list(mult=1), geom="errorbar", position = "identity", size=0.5, width=0.2) +
  stat_summary(fun.y = "mean", geom = "point", size=3, aes(shape=group,color=group)) + 
  scale_x_discrete(name = "Days after injection") +
  scale_y_continuous(name = "Weight (g)", limits=c(0, 4000), breaks = seq(0, 4000,500)) +
  scale_color_manual(values=c("green", "blue", "red"), name="Treatment", labels=c("A","B","C")) +
  scale_shape_manual(values=c(15,16,17), name  ="Treatment", labels=c("A", "B", "C")) +
  ggtitle("Weight variation over time") + theme(plot.title = element_text(hjust = 0.5)) +
  theme(legend.position = "right") + 
  theme(legend.background = element_rect(size=0.5, linetype="solid", color ="black", fill="white")) +
  theme(axis.line.x = element_line(size = 0.5, color = "black"),axis.text.x = element_text(color="black", size = 12),axis.line.y = element_line(size = 0.5, color = "black"),axis.text.y = element_text(color="black", size = 12),axis.title = element_text(size =15, face="bold"),plot.title = element_text(size =20, face = "bold"),panel.grid.major = element_line(color = "#F1F1F1"),panel.grid.minor = element_blank(), panel.background = element_blank()) +
  stat_smooth(se=F, aes(fill = group)) +
  scale_linetype_manual(values=c("dotted", "dotted", "dotted"))

感谢@PoGibas，我补充道

group=group，color=group

在ggplot的aes中，它给了我一个很好的结果

ggplot(datapoidsmono, aes(x = time, y = weight, group=group, color=group)) +
  stat_summary(aes(color = group), fun.data="mean_sdl", fun.args = list(mult=1), geom="errorbar", position = "identity", size=0.5, width=0.2) +
  stat_summary(fun.y = "mean", geom = "point", size=3, aes(shape=group,color=group)) + 
  scale_x_discrete(name = "Days after injection") +
  scale_y_continuous(name = "Weight (g)", limits=c(0, 4000), breaks = seq(0, 4000,500)) +
  scale_color_manual(values=c("green", "blue", "red"), name="Treatment", labels=c("A","B","C")) +
  scale_shape_manual(values=c(15,16,17), name  ="Treatment", labels=c("A", "B", "C")) +
  ggtitle("Weight variation over time") + theme(plot.title = element_text(hjust = 0.5)) +
  theme(legend.position = "right") + 
  theme(legend.background = element_rect(size=0.5, linetype="solid", color ="black", fill="white")) +
  theme(axis.line.x = element_line(size = 0.5, color = "black"),axis.text.x = element_text(color="black", size = 12),axis.line.y = element_line(size = 0.5, color = "black"),axis.text.y = element_text(color="black", size = 12),axis.title = element_text(size =15, face="bold"),plot.title = element_text(size =20, face = "bold"),panel.grid.major = element_line(color = "#F1F1F1"),panel.grid.minor = element_blank(), panel.background = element_blank()) +
  stat_smooth(se=F, linetype="dotted")

这是最后一张图表：

注：graphpad（见第一张图）提出的拟合比我最终选择的（黄土）拟合更平滑（method=“lm”，formula=y~x+I（x^2），size=1，se=FALSE），

，多亏了@PoGibas，我补充道

group=group，color=group

在ggplot的aes中，它给了我一个很好的结果

ggplot(datapoidsmono, aes(x = time, y = weight, group=group, color=group)) +
  stat_summary(aes(color = group), fun.data="mean_sdl", fun.args = list(mult=1), geom="errorbar", position = "identity", size=0.5, width=0.2) +
  stat_summary(fun.y = "mean", geom = "point", size=3, aes(shape=group,color=group)) + 
  scale_x_discrete(name = "Days after injection") +
  scale_y_continuous(name = "Weight (g)", limits=c(0, 4000), breaks = seq(0, 4000,500)) +
  scale_color_manual(values=c("green", "blue", "red"), name="Treatment", labels=c("A","B","C")) +
  scale_shape_manual(values=c(15,16,17), name  ="Treatment", labels=c("A", "B", "C")) +
  ggtitle("Weight variation over time") + theme(plot.title = element_text(hjust = 0.5)) +
  theme(legend.position = "right") + 
  theme(legend.background = element_rect(size=0.5, linetype="solid", color ="black", fill="white")) +
  theme(axis.line.x = element_line(size = 0.5, color = "black"),axis.text.x = element_text(color="black", size = 12),axis.line.y = element_line(size = 0.5, color = "black"),axis.text.y = element_text(color="black", size = 12),axis.title = element_text(size =15, face="bold"),plot.title = element_text(size =20, face = "bold"),panel.grid.major = element_line(color = "#F1F1F1"),panel.grid.minor = element_blank(), panel.background = element_blank()) +
  stat_smooth(se=F, linetype="dotted")

这是最后一张图表：

---

注：graphpad提出的拟合（见第一张图）比我最终选择的拟合（黄土）更为平滑（method=“lm”，formula=y~x+I（x^2），size=1，se=FALSE），

time
是一个连续变量吗？检查
class（datapoidmono$time）
[1]“因子”
我必须在main
aes
中转换因子以绘制绘图（见第一篇文章）
datapoidsmono$time Add
group=group
它将完成这一任务。
ggplot（datapoidsmono，aes（时间、重量、颜色=组、组=组））+
谢谢！的确，这是一个多么棘手的把戏！我自己不会发现的！我已经用实际的改进更新了第一篇帖子：）时间是一个连续变量吗？检查
class（datapoidsmono$time）
[1]“factor”
为了绘制绘图，我必须在factor中进行变换（见第一篇文章）
datapoidsmono$time在main
aes
中添加
group=group
，这样就可以了<代码>ggplot（数据点菜单，aes（时间，重量，颜色=组，组=组））+
谢谢！的确，这是一个多么狡猾的把戏！我自己也找不到！我已经用实际的改进更新了第一篇帖子：）
ggplot(datapoidsmono, aes(x = time, y = weight, group=group, color=group)) +
  stat_summary(aes(color = group), fun.data="mean_sdl", fun.args = list(mult=1), geom="errorbar", position = "identity", size=0.5, width=0.2) +
  stat_summary(fun.y = "mean", geom = "point", size=3, aes(shape=group,color=group)) + 
  scale_x_discrete(name = "Days after injection") +
  scale_y_continuous(name = "Weight (g)", limits=c(0, 4000), breaks = seq(0, 4000,500)) +
  scale_color_manual(values=c("green", "blue", "red"), name="Treatment", labels=c("A","B","C")) +
  scale_shape_manual(values=c(15,16,17), name  ="Treatment", labels=c("A", "B", "C")) +
  ggtitle("Weight variation over time") + theme(plot.title = element_text(hjust = 0.5)) +
  theme(legend.position = "right") + 
  theme(legend.background = element_rect(size=0.5, linetype="solid", color ="black", fill="white")) +
  theme(axis.line.x = element_line(size = 0.5, color = "black"),axis.text.x = element_text(color="black", size = 12),axis.line.y = element_line(size = 0.5, color = "black"),axis.text.y = element_text(color="black", size = 12),axis.title = element_text(size =15, face="bold"),plot.title = element_text(size =20, face = "bold"),panel.grid.major = element_line(color = "#F1F1F1"),panel.grid.minor = element_blank(), panel.background = element_blank()) +
  stat_smooth(se=F, linetype="dotted")