Description Usage Arguments Value References See Also
View source: R/select_cste_bin.R
select lasso penalty parameter λ for β_1 and β_2 in CSTE estimation.
1 2 3 4 5 6 7 8 9 10 | select_cste_bin(
x,
y,
z,
lam_seq,
beta_ini = NULL,
nknots = 1,
max.iter = 2000,
eps = 0.001
)
|
x |
samples of covariates which is a n*p matrix. |
y |
samples of binary outcome which is a n*1 vector. |
z |
samples of treatment indicator which is a n*1 vector. |
lam_seq |
a sequence for the choice of λ. |
beta_ini |
initial values for (β_1', β_2')', default value is NULL. |
nknots |
number of knots for the B-spline for estimating g_1 and g_2. |
max.iter |
maximum iteration for the algorithm. |
eps |
numeric scalar ≥q 0, the tolerance for the estimation of β_1 and β_2. |
A list which includes
optimal
: optimal cste within the given the sequence of λ.
bic
: BIC for the sequence of λ.
lam_seq
: the sequence of λ that is used.
Guo W., Zhou X. and Ma S. (2021). Estimation of Optimal Individualized Treatment Rules Using a Covariate-Specific Treatment Effect Curve with High-dimensional Covariates, Journal of the American Statistical Association, 116(533), 309-321
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