Description Usage Arguments Details Value Author(s) References See Also Examples
Replicates a small part the experiment presented in Cerioli et al. (2009), Tables 1 and 3, for the MCD using the maximum breakdown point fraction and a fraction of exactly 0.5.
1 | table13sim.parallel.check(cl, p, nn, N, B = 250, alpha = c(0.01, 0.025, 0.05), lgf = "", mlgf = "")
|
cl |
A cluster object, e.g., returned from |
p |
The dimension of the data used in each simulated run. |
nn |
The number of observations used in each simulated run. |
N |
The number of simulations to run. |
B |
The batch/block size: the number of simulations to run
in each block. This is useful when running very large
simulation runs ( |
alpha |
The significance level to use for detecting outliers. Can be a vector; the outlier detection tests will be run at each level. |
lgf |
Path to log file into which logging information should be written. |
mlgf |
not used at this time |
This is a variant of table13sim.parallel
designed
to investigate differences between the outlier detection tests with
the MCD when the data fraction is (a) the maximum breakdown point and
(b) exactly 0.5. It also checks whether the small-sample correction
was used in the results of Hardin and Rocke (2005) and Cerioli et
al. (2009).
This function is not really useful to anyone other than the author, and is not supported. Do not use it.
An array of dimension 3:
The results of each of the N
simulation runs appear along the first dimension.
The various estimators and tests appear along the second dimension. Results with suffix “T1” correspond to Table 1 of Cerioli et al. (2009) (the individual outlier tests) while those with suffix “T3” correspond to Table 3 (the simultaneous outlier tests). Currently the 26 columns appear in the following order.
Column Name | Covariate Estimate | Test Statistic |
"MCDMBP.RAW.T1" | MCD (max. breadown pt.) | chi-squared |
"MCDMBP.RAWGM.T1" | MCD (max. breadown pt.) | Green-Martin |
"MCDMBP.RAWHR.T1" | MCD (max. breadown pt.) | Hardin-Rocke |
"MCDMBP.RAWNOSSGM.T1" | MCD (max. breadown pt.), no small sample correction | Green-Martin |
"MCDMBP.RAWNOSSHR.T1" | MCD (max. breadown pt.), no small sample correction | Hardin-Rocke |
"RMCDMBP.T1" | reweighted MCD (max. breadown pt.) | chi-squared |
"MCDMBP.RAW.T3" | MCD (max. breadown pt.) | chi-squared |
"MCDMBP.RAWGM.T3" | MCD (max. breadown pt.) | Green-Martin |
"MCDMBP.RAWHR.T3" | MCD (max. breadown pt.) | Hardin-Rocke |
"MCDMBP.RAWNOSSGM.T3" | MCD (max. breadown pt.), no small sample correction | Green-Martin |
"MCDMBP.RAWNOSSHR.T3" | MCD (max. breadown pt.), no small sample correction | Hardin-Rocke |
"RMCDMBP.T3" | reweighted MCD (max. breadown pt.) | chi-squared |
"RMCDMBP.CH.T3" | reweighted MCD (max. breadown pt.) with Bonferroni correction | chi-squared |
"MCD50.RAW.T1" | MCD(0.50) | chi-squared |
"MCD50.RAWGM.T1" | MCD(0.50) | Green-Martin |
"MCD50.RAWHR.T1" | MCD(0.50) | Hardin-Rocke |
"MCD50.RAWNOSSGM.T1" | MCD(0.50), no small sample correction | Green-Martin |
"MCD50.RAWNOSSHR.T1" | MCD(0.50), no small sample correction | Hardin-Rocke |
"RMCD50.T1" | reweighted MCD(0.50) | chi-squared |
"MCD50.RAW.T3" | MCD(0.50) | chi-squared |
"MCD50.RAWGM.T3" | MCD(0.50) | Green-Martin |
"MCD50.RAWHR.T3" | MCD(0.50) | Hardin-Rocke |
"MCD50.RAWNOSSGM.T3" | MCD(0.50), no small sample correction | Green-Martin |
"MCD50.RAWNOSSHR.T3" | MCD(0.50), no small sample correction | Hardin-Rocke |
"RMCD50.T3" | reweighted MCD(0.50) | chi-squared |
"RMCD50.CH.T3" | reweighted MCD(0.50) with Bonferroni correction | chi-squared |
The specified values of alpha
correspond to the third
dimension; the dimnames will be of the form “alpha” + alpha
.
Written and maintained by Christopher G. Green <christopher.g.green@gmail.com>
Andrea Cerioli, Marco Riani, and Anthony C. Atkinson. Controlling the size of multivariate outlier tests with the mcd estimator of scatter. Statistical Computing, 19:341-353, 2009.
C. G. Green and R. Douglas Martin. An extension of a method of Hardin and Rocke, with an application to multivariate outlier detection via the IRMCD method of Cerioli. Working Paper, 2014. Available from http://students.washington.edu/cggreen/uwstat/papers/cerioli_extension.pdf
J. Hardin and D. M. Rocke. The distribution of robust distances. Journal of Computational and Graphical Statistics, 14:928-946, 2005.
1 2 3 4 | ## Not run:
#
## End(Not run)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.