Description Usage Arguments Details Value Author(s) References See Also
Computes a standarized or a sign-permutation based version of either the Single Tree Measure, the Quantitative Response Measure, or the Multiple Tree Measure.
1 2 3 4 | vim.norm(object, mu = 0)
vim.signperm(object, mu = 0, n.perm = 10000, n.subset = 1000,
version = 1, adjust = "bonferroni", rand = NA)
|
object |
either the output of |
mu |
a non-negative numeric value against which the importances are tested. See |
n.perm |
the number of sign permutations used in |
n.subset |
an integer specifying how many permutations should be considered at once. |
version |
either |
adjust |
character vector naming the method with which the raw permutation based
p-values are adjusted for multiplicity. If |
rand |
an integer for setting the random number generator in a reproducible case. |
In both 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.
An object of class logicFS
containing
primes |
the prime implicants, |
vim |
the respective importance of the prime implicants, |
prop |
NULL, |
type |
the type of model (1: classification, 2: linear regression, 3: logistic regression), |
param |
further parameters (if |
mat.imp |
NULL, |
measure |
the name of the used importance measure, |
useN |
the value of |
threshold |
the threshold suggested in |
mu |
|
Holger Schwender, holger.schwender@hhu.de
Schwender, H., Ruczinski, I., Ickstadt, K. (2011). Testing SNPs and Sets of SNPs for Importance in Association Studies. Biostatistics, 12, 18-32.
logic.bagging
, logicFS
,
vim.logicFS
, vim.chisq
, vim.ebam
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