Function reference • glmhd

All functions

adjust_binary(): Adjust the MLE in a binary regression

adjust_glm(): Estimate coefficients of a high-dimensional GLM

boot_fun(): Compute one bootstrap for a GLM

bootglm(): Compute resized bootstrap MLE for a GLM multiple times

compute_deriv(): Derivative of the negative log-likelihood

estimate_eta(): Estimate eta from MLE coef.

estimate_gamma(): Estimate the signal strength

estimate_variance(): Estimate std.dev. of the linear predictor evaluated at the MLE

find_param(): Solves a system of nonlinear equations

get_simulate_fun(): Simulate response given linear predictors

glm_boot(): Resized bootstrap method for a GLM

print(<glmadj>) summary(<glmadj>) print(<summary.glmadj>) predict(<glmadj>): Methods for adjusted glm objects

hinge(): Hinge function

integrate2_normal(): 2-dimensional Gaussian Expectation

lrt_glm(): LRT for high-dimensional glm

probe_frontier(): Estimate the problem dimension where two classes become linearly separable

prox_op(): One-dimensional proximal operator

rho_prime_logistic() f_prime1_logistic() f_prime0_logistic(): Logistic loss function

separable_proportion(): Porportion of linearly separable subsamples

signal_strength(): Estimate intercept and signal strength

solve_kappa() solve_beta() solve_gamma(): Compute the phase transition curve