Man pages for fdaoutlier
Outlier Detection Tools for Functional Data Analysis
| band_depth | Compute the band depth for a sample of curves/observations. |
| directional_quantile | Compute directional quantile outlyingness for a sample of... |
| dir_out | Dai & Genton (2019) Directional outlyingness for univariate... |
| extremal_depth | Compute extremal depth for functional data |
| extreme_rank_length | Compute the Extreme Rank Length Depth. |
| functional_boxplot | Functional Boxplot for a sample of functions. |
| hardin_factor_numeric | Compute F distribution factors for approximating the tail of... |
| linfinity_depth | Compute the L-infinity depth of a sample of curves/functions. |
| modified_band_depth | Compute the modified band depth for a sample of... |
| msplot | Outlier Detection using Magnitude-Shape Plot (MS-Plot) based... |
| muod | Massive Unsupervised Outlier Detection (MUOD) |
| plot_dtt | Plot Data from simulation models |
| projection_depth | Random projection for multivariate data |
| seq_transform | Find and classify outliers functional outliers using... |
| simulation_model1 | Convenience function for generating functional data |
| simulation_model2 | Convenience function for generating functional data |
| simulation_model3 | Convenience function for generating functional data |
| simulation_model4 | Convenience function for generating functional data |
| simulation_model5 | Convenience function for generating functional data |
| simulation_model6 | Convenience function for generating functional data |
| simulation_model7 | Convenience function for generating functional data |
| simulation_model8 | Convenience function for generating functional data |
| simulation_model9 | Convenience function for generating functional data |
| spanish_weather | Spanish Weather Data |
| total_variation_depth | Total Variation Depth and Modified Shape Similarity Index |
| tvdmss | Outlier detection using the total variation depth and... |
| world_population | World Population Data by Countries |
