Question

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)

Answer 1

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: