selbroken: Heuristic selection of the dimension of a PCA model with the...

In mlesnoff/rnirs: Dimension reduction, Regression and Discrimination for Chemometrics

Heuristic selection of the dimension of a PCA model with the broken-stick method

Description

The function helps selecting the dimension (i.e. nb. components) of a PCA model using the broken-stick method proposed by Frontier 1976.

The input matrix X is centered and scaled internally to the function. The eigenvalues are compared to the means of the length of ordered random sections of a stick of size = 1 (broken-stick distribution).

Usage

selbroken(X, ncomp, algo = NULL,
    plot = TRUE,
    xlab = "Nb. components", ylab = NULL,
    ...)

Arguments

X	A n x p matrix or data frame of variables.
ncomp	The maximal number of PCA scores (= components = latent variables) to be calculated.
algo	A function (algorithm) implementing a PCA. Default to NULL: if n < p, pca_eigenk is used; in the other case, pca_eigen is used.
plot	Logical. If TRUE (default), the results are plotted.
xlab	Label for the x-axis of the plot.
ylab	Label for the y-axis of the plot.
...	Optionnal arguments to pass in the function defined in algo.

Value

A list of several items, see the examples. Output opt is the selected number of components.

References

Bro, R., Smilde, A.K., 2014. Principal component analysis. Anal. Methods 6, 2812-2831. https://doi.org/10.1039/C3AY41907J

Dinno, A., 2009. Exploring the Sensitivity of Horn’s Parallel Analysis to the Distributional Form of Random Data. Multivariate Behavioral Research 44, 362-388. https://doi.org/10.1080/00273170902938969

Horn, J.L., 1965. A rationale and test for the number of factors in factor analysis. Psychometrika 30, 179-185. https://doi.org/10.1007/BF02289447

Jackson, D.A., 1993. Stopping Rules in Principal Components Analysis: A Comparison of Heuristical and Statistical Approaches. Ecology 74, 2204-2214. https://doi.org/10.2307/1939574

Examples

data(datoctane)
X <- datoctane$X
## removing outliers
zX <- X[-c(25:26, 36:39), ]
plotsp(zX)

ncomp <- 30
selbroken(zX, ncomp = ncomp)

mlesnoff/rnirs documentation built on April 24, 2023, 4:17 a.m.