vim.norm(object, mu = 0)
vim.signperm(object, mu = 0, n.perm = 10000, n.subset = 1000, version = 1, adjust = "bonferroni", rand = NA)
logicFS
or vim.logicFS
with addMatImp = TRUE
, or the output of logic.bagging
with importance = TRUE
and addMatImp = TRUE
.Details
.vim.signperm
.1
or 2
. If 1
, then the importance measure is computed
by 1 - padj, where padj is the adjusted p-value. If 2
, the importance measure is determined
by -log10(padj), where a raw p-value equal to 0 is set to 1 / (10 * n.perm
) to avoid
infinitive importances.
"qvalue"
, the function qvalue.cal
from the package siggenes
is used to compute q-values. Otherwise,
p.adjust
is used to adjust for multiple comparisons. See p.adjust
for all
other possible specifications of adjust
. If "none"
, the raw p-values will
be used. For more details, see Details
.logicFS
containing
addInfo = TRUE
),useN
from the original analysis with, e.g., logicFS
,Details
,mu
.vim.norm
and vim.signperm
, a paired t-statistic is computed for each
prime implicant, where the numerator is given by $VIM - $mu
with VIM being the
single or the multiple tree importance, and the denominator is the corresponding standard
error computed by employing the B
improvements of the considered prime implicant
in the B
logic regression models, where VIM is the mean over these
B
improvements.
Note that in the case of a quantitative response, such a standardization is not necessary.
Thus, vim.norm
returns a warning when the response is quantitative, and vim.signperm
does not divide $VIM - $mu
by its sample standard error.
Using mu = 0
might lead to calling a prime implicant important, even though it actually
shows only improvements of 1 or 0. When considering the prime implicants, it might be therefore
be helpful to set mu
to a value slightly larger than zero.
In vim.norm
, the value of this t-statistic is returned as the standardized importance
of a prime implicant. The larger this value, the more important is the prime implicant. (This applies
to all importance measures -- at least for those contained in this package.) Assuming normality,
a possible threshold for a prime implicant to be considered as important is the $1 - 0.05 / m$ quantile
of the t-distribution with $B - 1$ degrees of freedom, where $m$ is the number of prime implicants.
In vim.signperm
, the sign permutation is used to determine n.perm
permuted values of the
one-sample t-statistic, and to compute the raw p-values for each of the prime implicants. Afterwards,
these p-values are adjusted for multiple comparisons using the method specified by adjust
.
The permutation based importance of a prime implicant is then given by $1 -$ these adjusted p-values.
Here, a possible threshold for calling a prime implicant important is 0.95.
logic.bagging
, logicFS
,
vim.logicFS
, vim.chisq
, vim.ebam