`mvr`

and `mvrt.test`

functions for
mean-variance regularization and variance stabilization, and the computation of regularized test-statistics.
Returns optimal cluster configuration.
Internal function called by `mvr`

and internally by `mvrt`

.`MeanVarReg(data, nc.min, nc.max, probs, B, parallel, conf, verbose)`

data

`numeric`

data `matrix`

, where points to cluster are by rows (usually samples),
or an object that can be coerced to such a `matrix`

(such as a `vector`

or a `data.frame`

nc.min

Positive

`integer`

scalar of the minimum number of clusters.nc.max

Positive

`integer`

scalar of the maximum number of clusters.B

Positive

`integer`

scalar of the number of Monte Carlo replicates
of the inner loop of the sim statistic function.probs

`numeric`

`vector`

of probabilities for quantile diagnostic plots.parallel

`logical`

scalar. Is parallel computing to be performed? Optional, defaults to `FALSE`

.conf

verbose

`logical`

scalar. Is the output to be verbose?membership `numeric`

`vector`

of cluster membership of each variablenc Positive `integer`

scalar of number of clusters found in optimal cluster configurationgap `numeric`

`vector`

of the similarity statistic valuessde `numeric`

`vector`

of the standard errors of the similarity statistic valuesmu.quant `numeric`

`matrix`

(`nc.max`

-`nc.min`

+ 1) x (length(`probs`

)) of quantiles of meanssd.quant `numeric`

`matrix`

(`nc.max`

-`nc.min`

+ 1) x (length(`probs`

)) of quantiles of standard deviations

`mvr`

and `mvrt.test`

.- Dazard J-E., Hua Xu and J. S. Rao (2011). "
*R package MVR for Joint Adaptive Mean-Variance Regularization and Variance Stabilization.*" In JSM Proceedings, Section for Statistical Programmers and Analysts. Miami Beach, FL, USA: American Statistical Association IMS - JSM, 3849-3863. - Dazard J-E. and J. S. Rao (2012). "
*Joint Adaptive Mean-Variance Regularization and Variance Stabilization of High Dimensional Data.*" Comput. Statist. Data Anal. 56(7):2317-2333.