Description Usage Arguments Details Value Author(s) References Examples
For a given dataset, rFUNTA pseudo-depth values can be obtained. rFUNTA is a robustified functional data depth that is based on the intersection angles that the centered functions form with each other.
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Data |
a matrix. Enter the discretized values of a functional data set in a n times T matrix, where n is the number of functional observations and T is the number of time points. |
centered |
boolean. If the data are already centered, that means, the mean of each row of |
type.inner |
One of |
type.outer |
One of |
tick.dist |
atomic vector. The distance between two neighbored time points can be set here. Default value is |
nObs |
atomic vector. If the dataset has more than one dimension, specify |
The larger the value of FUNTA is, the less it can be regarded as a shape outlier, and vice versa. The values are bounded by 0 and 1.
Vector of rFUNTA values. First observation in Data
corresponds to first element of FUNTA
.
A. Rehage
Kuhnt, S.; Rehage, A. (2016) An angle-based multivariate functional pseudo-depth for shape outlier detection. Journal of Multivariate Analysis 146, 325-340.
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