tuneM {missRows} | R Documentation |
tuneM
can be used to determine the appropriate number
of imputed datasets needed to obtain satisfactory results
with MI-MFA.
tuneM(object, ncomp=2, Mmax=30, inc=5, N=10, tol=1e-06, showPlot=TRUE) ## S3 method for class 'tuneM' print(x, ...)
object |
an object of class |
x |
an object of class inheriting from |
ncomp |
a number of components to include in MFA. |
Mmax |
an integer corresponding to the maximum number of imputed datasets. See Details. |
inc |
integer. The increment of the sequence for the
number |
N |
integer. Collections of size |
tol |
a positive value, the tolerance used for assessing stabilization. |
showPlot |
logical. If |
... |
not currently used. |
The appropriate number of imputations can be informally determined by carrying out MI-MFA on N replicate sets of M_l imputations for l = 0, 1, 2, . . . , with M_0 < M_1 < M_2 < . . . < M_max, until the estimate compromise configurations are stabilized.
tuneM
function implements such a procedure. Collections
of size N
are generated for each number of imputations
M
, with M = seq(inc, Mmax, by = inc)
. The stability
of the estimated MI-MFA configurations is then determined by
calculating the RV coefficient between the configurations obtained
using M
_l and M
_{l+1}
imputations.
If showPlot = TRUE
a plot showing the stability of the
estimated MFA configurations is displayed. The values shown are
the mean RV coefficients for the N
configurations as a
function of the number of imputations. Error bars represent the
standard deviation of the RV coefficients.
A list with the following components:
stats |
a |
ggp |
an object of class |
Ignacio González, Valentin Voillet
Voillet V., Besse P., Liaubet L., Cristobal M.S., González I. (2016). Handling missing rows in multi-omics data integration: Multiple Imputation in Multiple Factor Analysis framework. BMC Bioinformatics, 17(40).
#-- load data and create MIDTList object data(NCI60) midt <- MIDTList(NCI60$mae) #-- tune the number of imputations ## Not run: tune <- tuneM(midt, ncomp=2, Mmax=100, inc=10, N=10) tune ## End(Not run)