Description Usage Arguments Value Examples
This transformation is three steps (1) Gaussianize the data, (2) zscore Transform the data, and (3) remove extreme outliers from the data. The sequence of these transformations helps focus further analyses on consequential variance in the data rather than having it be focused on variation resulting from the feature's measurement scale or outliers.
1 2 3 4 5 6 7 8 9 10 11 12 13 14  rrscale(
Y,
trans_list = list(box_cox_negative = box_cox_negative, asinh = asinh),
lims_list = list(box_cox_negative = c(100, 100), asinh = list(0, 100)),
opt_control = NULL,
opt_method = "DEoptim",
z = 4,
q = 0.001,
verbose = FALSE,
log_dir = ".rrscale/",
zeros = FALSE,
opts = FALSE,
seed = NULL
)

Y 
Data matrix, data.frame, or list of vectors, to be transformed. 
trans_list 
List of transformations to be considered. See function list_transformations. Each element of the list should be a list containing the transformation function as the first element and the derivative of the transformation function as the second argument. The first argument of each function should be the data, the second the transformation parameter. 
lims_list 
List of optimization limits for each transformation from trans_list. This should be a list the same length as 
opt_control 
Optional optimization controlling parameters for DEoptim control argument. See the DEoptim package for details. 
opt_method 
Which optimization method to use. Defaults to DEoptim. Other choice is nloptr. 
z 
The Ostep cutoff value. Points are removed if their robust zscore is above z in magnitude. 
q 
The Zstep winsorizing quantile cutoff. The quantile at which to winsorize the data when calculating the robust zscores. 
verbose 
a boolean, if TRUE then save optimization output in log_dir. 
log_dir 
directory for verbose output. Defaults to ".rrscale/" 
zeros 
How to deal with zeros in the data set. If set to FALSE the algorithm will fail if it encounters a zero. If set to a number or 'NA' then the zeros are replaced by this number or 'NA'. 
opts 
Boolean determining if optimization output is returned. Defaults to FALSE. 
seed 
Sets the seed before running any other analyses. 
A list of output:
opts: the optimization output for all transformation families and all columns
pars: the optimal parameters for each column for the optimal family
par_hat: the estimated optimal paramter
NT: the original data
RR: the robustrescaled data
G: gaussianized data
Z: robust ztransformed data
O: data with outliers removed
rr_fn: a function to apply the estimated RR transformation to new data. Takes arguments
Y: the data,
z: the zscore cutoff (defaults to 4),
q: the winsorizing quantile cutoff (defaults to 0.001),
lambda: the transformation parameter to use (defaults to the estimated one),
T: the transformation function family (defaults to the optimal estimated family),
mu: the mean to be used in the robust zscore step (reestimates if NULL)
sigma: the s.d. to be used in the robust zscore step (reestimates if NULL)
T: the optimal family
T_deriv: the derivative of the optimal family
T_name: name of the optimal family
alg_control: the parameters passed to the algorithm
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