Andrews plot

`andrewsplot(X)`

andrewsplot(X,...,'Standardize',* standopt*)

andrewsplot(X,...,'Quantile',alpha)

andrewsplot(X,...,'Group',group)

andrewsplot(X,...,

`'PropName'`

`PropVal`

h = andrewsplot(X,...)

`andrewsplot(X)`

creates an Andrews plot
of the multivariate data in the matrix `X`

. The rows
of `X`

correspond to observations, the columns to
variables. Andrews plots represent each observation by a function *f*(*t*)
of a continuous dummy variable *t* over the interval
[0,1]. *f*(*t*) is defined for the *i* th
observation in `X`

as

$$f(t)=X(i,1)/\sqrt{2}+X(i,2)\mathrm{sin}(2\pi t)+X(i,3)\mathrm{cos}(2\pi t)+\dots $$

`andrewsplot`

treats `NaN`

values
in `X`

as missing values and ignores the corresponding
rows.

`andrewsplot(X,...,'Standardize',`

creates
an Andrews plot where * standopt*)

`standopt`

`'on'`

— scales each column of`X`

to have mean`0`

and standard deviation`1`

before making the plot.`'PCA'`

— creates an Andrews plot from the principal component scores of`X`

, in order of decreasing eigenvalue. (See`pca`

.)`'PCAStd'`

— creates an Andrews plot using the standardized principal component scores. (See`pca`

.)

`andrewsplot(X,...,'Quantile',alpha)`

plots
only the median and the `alpha`

and (1 – `alpha`

)
quantiles of *f*(*t*) at each value
of *t*. This is useful if `X`

contains
many observations.

`andrewsplot(X,...,'Group',group)`

plots
the data in different groups with different colors. Groups are defined
by `group`

, a numeric array containing a group index
for each observation. `group`

can also be a categorical
array, character matrix, or cell array of character vectors containing
a group name for each observation.

`andrewsplot(X,...,`

sets
optional lineseries object properties to the specified values for
all lineseries objects created by * 'PropName'*,

`PropVal`

`andrewsplot`

.
(See Chart Line Properties.)`h = andrewsplot(X,...)`

returns a column
vector of handles to the lineseries objects created by `andrewsplot`

,
one handle per row of `X`

. If you use the `'Quantile'`

input
parameter, `h`

contains one handle for each of the
three lineseries objects created. If you use both the `'Quantile'`

and
the `'Group'`

input parameters, `h`

contains
three handles for each group.

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