# pdLMS: Plot frequency distributions(s) for given L, M and S values... In sitar: Super Imposition by Translation and Rotation Growth Curve Analysis

 pdLMS R Documentation

## Plot frequency distributions(s) for given L, M and S values in LMS method

### Description

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.

### Usage

``````pdLMS(
L = 1,
M = 1,
S = 0.2,
zcent = NULL,
zlim = 3.5,
N = 1000,
plot = TRUE,
...
)
``````

### Arguments

 `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 `par`) may also be supplied as arguments, particularly colour `col`, line type `lty`, line width `lwd` and character `pch`.

### Details

L, M and S should all be the same length, recycled if necessary.

### Value

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 `zcent` under each distribution.

The distributions can be plotted with `matplot(x, density, type='l')`.

### Author(s)

Tim Cole tim.cole@ucl.ac.uk

`z2cent`, `LMS2z`, `cLMS`

### Examples

``````
## 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)

``````

sitar documentation built on July 9, 2023, 6:51 p.m.