GE_nleqslv | R Documentation |
GE_nleqslv.R #' Uses package nleqslv to get a numerical solution to the score equations, which we can use to check our direct solution from GE_bias().
GE_nleqslv(beta_list, cov_list, cov_mat_list, mu_list, HOM_list)
beta_list |
A list of the effect sizes in the true model. Use the order beta_0, beta_G, beta_E, beta_I, beta_Z, beta_M. If G or Z or M is a vector, then beta_G/beta_Z/beta_M should be vectors. If Z and/or M/W do not exist in your model, then set beta_Z and/or beta_M = 0. |
cov_list |
A list of expectations (which happen to be covariances if all covariates are centered at 0) in the order specified by GE_enumerate_inputs(). If Z and/or M/W do not exist in your model, then treat them as constants 0. For example, if Z doesn't exist and W includes 2 covariates, then set cov(EZ) = 0 and cov(ZW) = (0,0). If describing expectations relating two vectors, i.e. Z includes two covariates and W includes three covariates, sort by the first term and then the second. Thus in the example, the first three terms of cov(ZW) are cov(Z_1,W_1),cov(Z_1,W_2), cov(Z_1,W_3), and the last three terms are cov(Z_3,W_1), cov(Z_3,W_2), cov(Z_3,W_3). |
cov_mat_list |
A list of matrices of expectations as specified by GE_enumerate_inputs(). |
mu_list |
A list of means as specified by GE_enumerate_inputs(). |
HOM_list |
A list of higher order moments as specified by GE_enumerate_inputs(). |
A list of the fitted coefficients alpha
solutions <- GE_bias_normal_squaredmis( beta_list=as.list(runif(n=6, min=0, max=1)), rho_list=as.list(rep(0.3,6)), prob_G=0.3, cov_Z=1, cov_W=1) GE_nleqslv(beta_list=solutions$beta_list, solutions$cov_list, solutions$cov_mat_list, solutions$mu_list, solutions$HOM_list)
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