Introduction

As was expected, the runderiv() function has been both useful and deficient. Useful because it offers a good replacement for smooth.spline() calculations of derivatives for things like N^2. And deficient because it only calculated derivatives, not values!

Both an extension and a renaming were called for. The result is runlm().

Tests

Below are the examples from its manpage, with the results.

Case 1

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library(oce)

## Loading required package: methods
## Loading required package: mapproj
## Loading required package: maps

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x <- 1:100
y <- 1 + x/100 + sin(x/5)
yn <- y + rnorm(100, sd = 0.1)
L <- 4
calc <- runlm(x, y, L = L, deriv = 0)
plot(x, y, type = "l", lwd = 7, col = "gray")
points(x, yn, pch = 20, col = "blue")
lines(x, calc, lwd = 2, col = "red")

Case 2

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data(ctd)
plot(ctd, which = "N2")
rho <- swRho(ctd)
z <- swZ(ctd)
zz <- seq(min(z), max(z), 0.1)
N2 <- -9.8/mean(rho) * runlm(z, rho, zz, deriv = 1)
lines(N2, -zz, col = "red")
legend("bottomright", lwd = 2, bg = "white", col = c("black", "red"), legend = c("swN2()", 
    "using runlm()"))

Comments

1. The fit in Case 1 is almost spookily good.

2. The N^2 results suggest including this as a method for swN2(), perhaps the default method, but that’s for another day.

Resources

• Source code: 2014-04-11-runlm.R