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Simulate a data set with binary response following the logistic regression model.
gen.binomial.data(n, p, rho = 0, kappa = 5, beta.type = 1, seed = 2021)A list containing the simulated data.
the covariate matrix, of dimension n x p.
the response, of length n.
the true coefficients, of length p.
Sample size.
Number of covariates.
The parameter defining the AR(1) correlation matrix.
The number of nonzero coefficients.
Numeric indicator for choosing the beta type. For
beta.type = 1, the true coefficient vector has kappa components being 1,
roughly equally distributed between 1 to p. For beta.type = 2,
the first kappa values are 1, and the rest are 0. For beta.type = 3,
the first kappa values are equally-spaced values from 10 to 0.5, and
the rest are 0. For beta.type = 4, the first kappa values are
the first kappa values in c(-10, -6, -2, 2, 6, 10), and the rest are
0. For beta.type = 5, the first kappa values are 1, and the
rest decay exponentially to 0 with base 0.5.
The seed for reproducibility. Default is 2021.
bin_data <- gen.binomial.data(n = 200, p = 20, seed = 2021)
head(bin_data$X)
head(bin_data$y)
head(bin_data$beta)
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