How can I add RMSE, slope, intercept and r^2 to a plot using R? I have attached a script with sample data, which is a similar format to my real dataset--unfortunately, I am at a stand-still. Is there an easier way to add these statistics to the graph than to create an object from an equation and insert that into text()
? I would ideally like the statistics to be displayed stacked on the graph. How can I accomplish this?
## Generate Sample Data
x = c(2,4,6,8,9,4,5,7,8,9,10)
y = c(4,7,6,5,8,9,5,6,7,9,10)
# Create a dataframe to resemble existing data
mydata = data.frame(x,y)
#Plot the data
plot(mydata$x,mydata$y)
abline(fit <- lm(y~x))
# Calculate RMSE
model = sqrt(deviance(fit)/df.residual(fit))
# Add RMSE value to plot
text(3,9,model)
Here is a version using base graphics and ?plotmath
to draw the plot and annotate it
## Generate Sample Data
x = c(2,4,6,8,9,4,5,7,8,9,10)
y = c(4,7,6,5,8,9,5,6,7,9,10)
## Create a dataframe to resemble existing data
mydata = data.frame(x,y)
## fit model
fit <- lm(y~x, data = mydata)
Next calculate the values you want to appear in the annotation. I prefer bquote()
for this, where anything marked-up in .(foo)
will be replaced by the value of the object foo
. The Answer @mnel points you to in the comments uses substitute()
to achieve the same thing but via different means. So I create objects in the workspace for each value you might wish to display in the annotation:
## Calculate RMSE and other values
rmse <- round(sqrt(mean(resid(fit)^2)), 2)
coefs <- coef(fit)
b0 <- round(coefs[1], 2)
b1 <- round(coefs[2],2)
r2 <- round(summary(fit)$r.squared, 2)
Now build up the equation using constructs described in ?plotmath
:
eqn <- bquote(italic(y) == .(b0) + .(b1)*italic(x) * "," ~~
r^2 == .(r2) * "," ~~ RMSE == .(rmse))
Once that is done you can draw the plot and annotate it with your expression
## Plot the data
plot(y ~ x, data = mydata)
abline(fit)
text(2, 10, eqn, pos = 4)
Which gives:
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