Description Usage Arguments Value Author(s) References See Also
Identification of interactions of binary variables associated with survival time using logic regression.
1 2 3 4 5 6 7 8 9 10 11 12 13  ## Default S3 method:
survivalFS(x, y, B = 20, replace = FALSE,
sub.frac = 0.632, score = c("DPO", "Conc", "Brier", "PL"),
addMatImp = TRUE, adjusted = FALSE, neighbor = NULL,
ensemble = FALSE, rand = NULL, ...)
## S3 method for class 'formula'
survivalFS(formula, data, recdom = TRUE, ...)
## S3 method for class 'logicBagg'
survivalFS(x, score = c("DPO", "Conc", "Brier", "PL"),
adjusted = FALSE, neighbor = NULL, ensemble = FALSE,
addMatImp = TRUE, rand = NULL, ...)

x 
a matrix consisting of 0's and 1's. Alternatively, 
y 
a vector of class 
B 
an integer specifying the number of iterations. 
replace 
should sampling of the cases be done with replacement? If

sub.frac 
a proportion specifying the fraction of the observations that
are used in each iteration to build a classification rule if 
score 
a character string naming the score that should be used in the computation of the importance measure for a survival time analysis. By default, the distance between predicted outcomes ( 
addMatImp 
should the matrix containing the improvements due to the prime implicants
in each of the iterations be added to the output if 
adjusted 
logical specifying whether the measures should be adjusted for noise. Often, the interaction actually associated with the response is not exactly found in some iterations of logic bagging, but an interaction is identified that additionally contains one (or seldomly more) noise SNPs. If 
neighbor 
a list consisting of character vectors specifying SNPs that are in LD. If specified, all SNPs need to occur exactly one time in this list. If specified, the importance measures are adjusted for LD by considering the SNPs within a LD block as exchangable. 
ensemble 
in the case of a survival outcome, should 
rand 
numeric value. If specified, the random number generator will be set into a reproducible state. 
formula 
an object of class 
data 
a data frame containing the variables in the model. Each row of 
recdom 
a logical value or vector of length 
... 
further arguments of 
An object of class logicFS
containing
primes 
the prime implicants, 
vim 
the importance of the prime implicants, 
prop 
the proportion of logic regression models containing the prime implicants, (or the neighbors of the prime implicants, if 
type 
the type of model (1: classification, 2: linear regression, 3: logistic regression, 4: Cox regression), 
param 
further parameters (if 
mat.imp 
either the matrix containing the improvements if 
measure 
the name of the used importance measure, 
neighbor 

useN 
the value of 
threshold 
NULL, 
mu 
NULL. 
Tobias Tietz, tobias.tietz@hhu.de
Tietz, T., Selinski, S., Golka, K., Hengstler, J.G., Gripp, S., Ickstadt, K., Ruczinski, I., Schwender, H. (2018). Identification of Interactions of Binary Variables Associated with Survival Time Using survivalFS. Submitted.
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