miaSpectra2D {ChemoSpec2D} | R Documentation |

## Multivariate Image Analysis (Tucker 1) of a Spectra2D Object

### Description

Carry out multivariate image analysis of a `Spectra2D`

object
(multivariate image analysis is the same as a Tucker1 analysis).
Function `pcasup1`

from package ThreeWay is used.

### Usage

```
miaSpectra2D(spectra)
```

### Arguments

`spectra` |
An object of S3 class |

### Value

A list per `pcasup1`

. Of particular interest are the
elements `C`

containing the eigenvectors and `1c`

containing the eigenvalues.
We add the class `mia`

to the list for our use later, as well as a `method`

element for annotating plots.

### Author(s)

Bryan A. Hanson, DePauw University.

### References

A. Smilde, R. Bro and P. Geladi "Multi-way Analysis: Applications in the Chemical Sciences" Wiley (2004). See especially Example 4.5.

P. Geladi and H. Grahn "Multivariate Image Analysis" Wiley (1996). Note that in this text the meanings of scores and loadings are reversed from the usual spectroscopic uses of the terms.

### See Also

For other data reduction methods for `Spectra2D`

objects, see
`pfacSpectra2D`

and `popSpectra2D`

.

### Examples

```
library("ggplot2")
data(MUD1)
res <- miaSpectra2D(MUD1)
# plotScores & plotScree use ggplot2 graphics
p1 <- plotScores(MUD1, res, tol = 1.0, ellipse = "cls")
p1 <- p1 + ggtitle("MIA Scores")
p1
p2 <- plotScree(res)
p2
# plotLoadings2D uses base graphics
MUD1a <- plotLoadings2D(MUD1, res,
load_lvls = seq(-90, 0, 10),
main = "MIA Comp. 1 Loadings"
)
# Selection of loading matrix levels can be aided by the following
# Use MUD1a$names to find the index of the loadings
inspectLvls(MUD1a,
which = 11, ylim = c(0, 80),
main = "Histogram of Loadings Matrix"
)
```

*ChemoSpec2D*version 0.5.0 Index]