fsdaR v0.4-9
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Robust Data Analysis Through Monitoring and Dynamic Visualization
Provides interface to the 'MATLAB' toolbox 'Flexible Statistical Data Analysis
(FSDA)' which is a comprehensive and computationally efficient
software package for robust statistics in regression, multivariate
and categorical data analysis. The current R version implements tools
for regression: (forward search, S- and MM-estimation, least trimmed
squares (LTS) and least median of squares (LMS)), for multivariate analysis
(forward search, S- and MM-estimation), for cluster analysis and cluster-wise regression.
The distinctive feature of our package is the possibility of
monitoring the statistics of interest as function of breakdown point,
efficiency or subset size, depending on the estimator. This is
accompanied by a rich set of graphical features, such as dynamic
brushing, linking, particularly useful for exploratory data analysis.
Functions in fsdaR
| Name | Description | |
| LXS_control | Creates an LSX_control object | |
| Sreg_control | Creates an Sreg_control object | |
| Sregeda_control | Creates an Sregeda_control object | |
| fsmeda.object | Description of fsmeda.object Objects | |
| carbikeplot | Produces the carbike plot to find best relevant clustering solutions obtained by tclustICsol | |
| corfwdplot | Monitoring the correlations between consecutive distances or residuals | |
| fsmmmdrs | Performs random start monitoring of minimum Mahalanobis distance | |
| fsdalts.object | Description of fsdalts Objects | |
| fsdalms.object | Description of fsdalms Objects | |
| MMregeda_control | Creates an MMregeda_control object | |
| MMreg_control | Creates an MMreg_control object | |
| diabetes | Diabetes data | |
| emilia2001 | Demographic data from the 341 miniciplaities in Emilia Romagna (an Italian region). | |
| M5data | Mixture M5 Data. | |
| FSReda_control | Creates an FSReda_control object | |
| fsmult.object | Description of fsmult.object Objects | |
| FSR_control | Creates an FSR_control object | |
| fsr.object | Description of fsr Objects | |
| fsmult | Gives an automatic outlier detection procedure in multivariate analysis | |
| fsmmmdrs.object | Description of fsmmmdrs.object Objects | |
| malindexplot | Plots the trajectory of minimum Mahalanobis distance (mmd) | |
| geyser2 | Old Faithful Geyser Data. | |
| mdrplot | Plots the trajectory of minimum deletion residual (mdr) | |
| malfwdplot | Plots the trajectories of scaled Mahalanobis distances along the search | |
| levfwdplot | Plots the trajectories of the monitored scaled (squared) residuals | |
| loyalty | Loyalty data | |
| mmdrsplot | Plots the trajectories of minimum Mahalanobis distances from different starting points | |
| mmdplot | Plots the trajectory of minimum Mahalanobis distance (mmd) | |
| resindexplot | Plots the residuals from a regression analysis versus index number or any other variable | |
| fsreg | fsreg: an automatic outlier detection procedure in linear regression | |
| smult.object | Description of smult.object Objects | |
| fsreda.object | Description of fsreda Objects | |
| smulteda.object | Description of smulteda.object Objects | |
| mmregeda.object | Description of mmregeda Objects | |
| resfwdplot | Plots the trajectories of the monitored scaled (squared) residuals | |
| mmmulteda.object | Description of mmmulteda.object Objects | |
| mmreg.object | Description of mmreg Objects | |
| smult | Computes S estimators in multivariate analysis | |
| mmmult | Computes MM estimators in multivariate analysis with auxiliary S-scale | |
| mmmult.object | Description of mmmult.object Objects | |
| swissbanknotes | Swiss banknote data | |
| summary.fsdalts | Summary Method for fsdalts objects | |
| tclustICsol | Extracts a set of best relevant solutions obtained by tclustIC | |
| tclustICplot | Plots information criterion as a function of c and k, based on the solutions obtained by tclustIC | |
| swissheads | Swiss banknote data | |
| tclustIC | Performs cluster analysis by calling tclustfsda for different number of groups k and restriction factors c | |
| tclusteda.object | Objects returned by the function tclustfsda with the option monitoring=TRUE | |
| tclustfsda | Computes trimmed clustering with scatter restrictions | |
| summary.fsr | Summary Method for FSR objects | |
| tclustfsda.object | Objects returned by the function tclustfsda | |
| tclustic.object | Objects returned by the function tclustIC | |
| sregeda.object | Description of sregeda Objects | |
| sreg.object | Description of sreg Objects | |
| summary.fsdalms | Summary Method for fsdalms objects | |
| tclusticsol.object | Objects returned by the function tclustICsol | |
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Details
| Date | 2020-01-13 |
| VersionNote | Released 0.4-8 on 2020-01-13 on CRAN |
| SystemRequirements | (license-free) MATLAB Runtime (MCR) V 9.6, Java (>=8) |
| LazyLoad | yes |
| LazyData | yes |
| License | GPL (>= 2) |
| Packaged | 2020-01-14 12:53:15 UTC; todorovv |
| NeedsCompilation | no |
| Repository | CRAN |
| RoxygenNote | 7.0.2 |
| Date/Publication | 2020-01-14 16:40:02 UTC |
| imports | ggplot2 , methods , rJava , stats4 |
| suggests | MASS |
| depends | R (>= 3.5.0) , rrcov |
| Contributors | Emmanuele Sordini, Aldo Corbellini, Francesca Torti, Marco Riani, Domenico Perrotta, Andrea Cerioli |
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