T. Beige - 10 months ago 53

R Question

**Edit:**

`x = c(324, 219, 406, 273, 406, 406, 406, 406, 406, 168, 406, 273, 168, 406, 273, 168, 219, 324, 324, 406, 406, 406, 273, 273, 324, 324, 219, 273, 219, 273, 273, 324, 273, 324, 324, 406, 219, 406, 273, 273, 406, 219, 324, 273, 324, 406, 219, 324, 219, 324, 324, 406, 406, 406, 324, 273, 273, 219, 219, 324, 273, 324, 324, 219, 324, 219, 324, 219, 219, 324, 273, 406, 406, 273, 324, 273, 273, 219, 406, 273, 273, 324, 324, 324, 324, 324, 406, 324, 273, 406, 406, 219, 219, 324, 273, 406, 324, 324, 324, 324)`

y = c(68,121,NA,87,NA,17,20,15,17,146,25,91,141,24,88,143,120,63,62,16,21,20,83,88,65,63,124,88,120,91,85,65,91,63,69,23,115,23,87,90,20,120,65,90,65,20,120,60,110,60,17,20,20,20,68,80,87,124,121,65,85,67,60,115,60,120,66,121,117,68,90,17,23,90,61,80,88,121,NA,91,88,62,60,70,60,60,27,76,96,23,20,113,118,60,91,23,60,60,65,70)

data = data.frame(x,y)

I create the following graphic with

`ggplot2`

`geom_smooth()`

`g = ggplot(data, aes(x,y)) +`

geom_point() +

geom_smooth(method="loess") +

geom_smooth(method="lm", col="red")

My data contains variables x (has got only 9 values) and y (metrical). Now I want to add the projection points of the

`loess`

`loes = loess(data$y ~ data$x)`

RR = sort(unique(predict(loes)), decreasing=TRUE) # y coordinates

LL = unique(x, fromLast=TRUE) # x coordinates

Now I add these projection points to my plot.

`g + geom_point(aes(y=RR[1], x=LL[1]), col="blue", size=2, shape=18) +`

geom_point(aes(y=RR[2], x=LL[2]), col="blue", size=2, shape=18) +

geom_point(aes(y=RR[3], x=LL[3]), col="blue", size=2, shape=18) +

geom_point(aes(y=RR[4], x=LL[4]), col="blue", size=2, shape=18) +

geom_point(aes(y=RR[5], x=LL[5]), col="blue", size=2, shape=18)

`loess`

`loess`

Example Image

Answer Source

The error is in these lines:

```
loes = loess(y ~ x, data = data)
RR = sort(unique(predict(loes)), decreasing=TRUE) # y coordinates
LL = unique(x, fromLast=TRUE) # x coordinates
```

The prediction is made using the same function, but out of order. You should use `newdata`

to appropriately match the prediction with the predictors.

```
g = ggplot(data, aes(x,y)) +
geom_smooth(method="loess", color = "red")
RR <- predict(loes, newdata = data.frame(x = unique(x)))
g + annotate("point", x = unique(x), y = RR)
```