simBinomial: Simulated data from the binary logistic regression model
In icmm: Empirical Bayes Variable Selection via ICM/M Algorithm
Description
Usage
Format
Examples
Description
Simulated data from the binary logistic regression model. A data frame with 100 observations and 401 variables. The included variables are
V1 A numeric vector of binary responses where each entry is either 0 or 1.
V2-V401 400 vectors of covariates.
Usage
1
Format
A data frame of simulated data from the binary logistic regression with 100 observations and 401 variables.
Examples
1
2
3
data(simBinomial)
Y<-as.matrix(simBinomial[,1])
X<-as.matrix(simBinomial[,-1])
Example output
icmm documentation built on May 26, 2021, 9:06 a.m.
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Description Usage Format Examples
Description
Simulated data from the binary logistic regression model. A data frame with 100 observations and 401 variables. The included variables are
V1 A numeric vector of binary responses where each entry is either 0 or 1.
V2-V401 400 vectors of covariates.
Usage
1 |
Format
A data frame of simulated data from the binary logistic regression with 100 observations and 401 variables.
Examples
1 2 3 | data(simBinomial)
Y<-as.matrix(simBinomial[,1])
X<-as.matrix(simBinomial[,-1])
|
Example output
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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