Usage
apple(X, y, family="binomial", penalty = "LASSO", gamma, cha.poi = 1,
eps = 1e-15, lam.list, lambda.min.ratio, max.iter = 100, max.num,
n.lambda = 100)
Arguments
X
input matrix, of dimension nobs x nvars; each row is an observation vector.
y
response variable, of dimension nobs x 1. non-negative counts for family="poisson", binary for family="binomial".
penalty
LASSO and MCP are provided.
gamma
the MCP concavity parameter.
cha.poi
the value used to change from Newton Raphson correction to Coordinate Descent correction, which is the $\alpha$ in the following inequality, $k> \alpha\sqrt{n}$, where $k$ is the size of current active set. when this inequality holds, the correction method changes from Newton Raphson to Coordinate Descent.
eps
the precision used to test the convergence.
lam.list
a user supplied $\lambda$ sequence. typical usage is to have the program compute its own lambda sequence based on lambda.min.ratio and n.lambda. supplying a value of $\lambda$ overrides this.
lambda.min.ratio
optional input. smallest value for lambda, as a fraction of max.lam, the (data derived) entry value. the default depends on the sample size n relative to the number of variables p. if n > p, the default is 0.0001. otherwise, the default is 0.01.
max.iter
maximum number of iteration in the computation.
max.num
optional input. maximum number of nonzero coefficients.
n.lambda
the number of lambda values.