upper {holiglm} | R Documentation |
Upper Bound
Description
Set a upper bound on the coefficient of specific covariates.
Usage
upper(kvars)
Arguments
kvars |
a named vector giving the upper bounds. The names should correspond to the names of the covariates in the model matrix. |
Value
A holistic generalized model constraint, object inheriting from class "hglmc"
.
References
McDonald, J. W., & Diamond, I. D. (1990). On the Fitting of Generalized Linear Models with Nonnegativity Parameter Constraints. Biometrics, 46 (1): 201–206. doi:10.2307/2531643
Slawski, M., & Hein, M. (2013). Non-negative least squares for high-dimensional linear models: Consistency and sparse recovery without regularization. Electronic Journal of Statistics, 7: 3004-3056. doi:10.1214/13-EJS868
See Also
Other Constraint-Constructors:
group_equal()
,
group_inout()
,
group_sparsity()
,
include()
,
k_max()
,
linear()
,
lower()
,
pairwise_sign_coherence()
,
rho_max()
,
sign_coherence()
Examples
dat <- rhglm(100, c(1, 2, -3, 4, 5, -6))
constraints <- upper(c(x1 = 0, x4 = 1))
hglm(y ~ ., constraints = constraints, data = dat)