pdLMS | R Documentation |
The LMS method defines frequency distributions in terms of L, M and S parameters.
pdLMS
plots one or more LMS distributions and optionally returns specified
centiles on each distribution.
pdLMS( L = 1, M = 1, S = 0.2, zcent = NULL, zlim = 3.5, N = 1000, plot = TRUE, ... )
L |
vector of Box-Cox transformation (lambda) values, L in the LMS method (default 1 corresponding to the Normal distribution). |
M |
vector of medians (mu), M in the LMS method (default 1). |
S |
vector of coefficients of variation (sigma), S in the LMS method (default 0.2). |
zcent |
optional vector of z-scores for conversion to the measurement scale under each distribution. |
zlim |
scalar defining z-score limits underlying x-axis (default 3.5). |
N |
number of points per distribution curve (default 1000). |
plot |
logical for plotting (default TRUE). |
... |
Further graphical parameters (see |
L, M and S should all be the same length, recycled if necessary.
An invisible list with the following components:
x |
vector of x values for plotting. |
density |
matrix of densities for each distribution. |
centile |
matrix of measurement centiles corresponding to |
The distributions can be plotted with matplot(x, density, type='l')
.
Tim Cole tim.cole@ucl.ac.uk
z2cent
, LMS2z
, cLMS
## plot normal distribution pdLMS() ## compare variety of distributions ## with centiles corresponding to +3 z-scores pdLMS(L=-2:3, M=2:3, S=1:3/10, zcent=3, lty=1)
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