mvoutlier: Multivariate outlier detection based on robust methods

ロバストな手法に基づく多変量外れ値検知

> library(mvoutlier)

Loading required package: sgeostat

sROC 0.1-2 loaded

バージョン: 2.0.8

関数名	概略
`X`	Data (X coordinate) of illustrative example in paper (see below)
`Y`	Data (Y coordinate) of illustrative example in paper (see below)
`aq.plot`	Adjusted Quantile Plot
`arw`	Adaptive reweighted estimator for multivariate location and scatter
`bhorizon`	B-horizon of the Kola Data
`bss.background`	Background map for the BSS project
`bssbot`	Bottom Layer of the BSS Data
`bsstop`	Top Layer of the BSS Data
`chisq.plot`	Chi-Square Plot
`chorizon`	C-horizon of the Kola Data
`color.plot`	Color Plot
`corr.plot`	Correlation Plot: robust versus classical bivariate correlation
`dat`	Data of illustrative example in paper (see below)
`dd.plot`	Distance-Distance Plot
`humus`	Humus Layer (O-horizon) of the Kola Data
`kola.background`	Background map for the Kola project
`locoutNeighbor`	Diagnostic plot for identifying local outliers with varying size of neighborhood
`locoutPercent`	Diagnostic plot for identifying local outliers with fixed size of neighborhood
`locoutSort`	Interactive diagnostic plot for identifying local outliers
`map.plot`	Plot Multivariate Outliers in a Map
`moss`	Moss Layer of the Kola Data
`mvoutlier.CoDa`	Interpreting multivatiate outliers of CoDa
`pbb`	BSS background Plot
`pcout`	PCOut Method for Outlier Identification in High Dimensions
`pkb`	Kola background Plot
`plot.mvoutlierCoDa`	Plots for interpreting multivatiate outliers of CoDa
`sign1`	Sign Method for Outlier Identification in High Dimensions - Simple Version
`sign2`	Sign Method for Outlier Identification in High Dimensions - Sophisticated Version
`symbol.plot`	Symbol Plot
`uni.plot`	Univariate Presentation of Multivariate Outliers