Saul Garcia - 25 days ago 17
R Question

# Understanding the Local Polynomial Regression

Could someone explain me why I get different lines when I plot? Somehow I thought the line should be the same

``````    data(aircraft)
help(aircraft)
attach(aircraft)

lgWeight <- log(Weight)

library(KernSmooth)

# a) Fit a nonparametric regression to data (xi,yi) and save the estimated values mˆ (xi).

# Regression of degree 2 polynomial of lgWeight against Yr
op <- par(mfrow=c(2,1))
lpr1 <- locpoly(Yr,lgWeight, bandwidth=7, degree = 2, gridsize = length(Yr))
plot(Yr,lgWeight,col="grey", ylab="Log(Weight)", xlab = "Year")
lines(lpr1,lwd=2, col="blue")
lines(lpr1\$y, col="black")
``````

How can I get the values from the model? If I print the model, it gives me the values on
`\$x`
and
`\$y`
, but somehow if I plot them, is not the same as the blue line. I need the values of the fitted model (blue) for every
`x`
, could someone help me?

The fitted model (blue curve) is correctly in `lpr1`. As you said, the correct y-values are in `lpr1\$y` and the correct x-values are in `lpr1\$x`.
The reason the second plot looks like a straight line is because you are only giving the `plot` function one variable, `lpr1\$y`. Since you don't specify the x-coordinates, R will automatically plot them along an index, from 1 to the length of the y variable.
``````lines(x = lpr1\$x, y = lpr1\$y,lwd=2, col="blue")  # plots curve