fit.sensitivity.plot {breakage} | R Documentation |
Plots a contour map of the sensitivity of the residual error of a breakage resistance model to variation of the fitted parameters. This should give some idea of the goodness of the fit.
fit.sensitivity.plot(data, fit, rho = 51, l = 1000, r.range = 0.015, theta.range = pi/360, steps = 100, nlevels = 200, r.squared = TRUE, bound.at = 0.99, ...)
data |
Measured breakage data as an XY list or data frame, with |
fit |
The fitting results list returned by |
rho |
Resistivity of the filler solution, in ohm centimetres. Must be the same value used for fitting or the plot will be incorrect. |
l |
The initial length of the pipette tip, in microns. Must be the same value used for fitting or the plot will be incorrect. |
r.range |
The range above and below the fitted inner radius result, |
theta.range |
The range above and below the fitted half-cone angle result, |
steps |
The total number of steps to evaluate in both directions. |
nlevels |
The number of contour lines to draw. |
r.squared |
Whether to plot the error value directly, or transform it to plot the coefficient of determination (or R-squared) instead. The latter is plotted by default. It contains the same information in marginally more convenient form, but its use might be considered misleading if taken as implying a linear model. |
bound.at |
A level at which to plot a significance contour. This is on top of the |
... |
Any additional parameters to be passed to the main |
x |
The x (theta) values of the plotted surface. |
y |
The y (radius) values of the plotted surface. |
z |
The z (error) values of the plotted surface. |
Matthew Caldwell
# fake up some breakage data brks <- sort(abs(0.5 + rnorm(n=15, sd=0.5) * 1:15)) res <- resist.breakage(brks, theta=3*pi/180, r=0.04, rho=64) + rnorm(15) dat <- list(x=brks, y=res) # fit it fit <- fit.breakage(dat, do.plot=FALSE) # plot the sensitivity surface fit.sensitivity.plot(dat, fit)