backStepIter: backwards removes \beta_i in model Y \sim N(X \beta + X...

In JonasWallin/PolyMixed:

backwards removes \beta_i in model Y \sim N(X \beta + X \gamma, \sigma_Y^2 I_n \times n) \gamma \sim N(u, \tau^2 I_p \times p) u = [u_1,...,u_n_c] u_i \sim N(\mu_0, \sigma^2_u 1 backStepIter( Y, X, model = c("simple", "constant"), betas, critval = qnorm(1 - (1 - 0.95)/2), nc = NULL, return_full = FALSE, SVDX = NULL ) \itemY- (n x 1) observations \itemX- (n x p) covariates \itemmodel- (string) simple - simpliefed model (sigma^2_u = 0) constant - the full model \itemcritval- (double) value to minimum accepted level \itemnc- (int) number of chromosones \itemreturn_full- (bool) return either betas or betas and params betas - (p x 1) vector of the beta values backwards removes \beta_i in model Y \sim N(X \beta + X \gamma, \sigma_Y^2 I_n \times n) \gamma \sim N(u, \tau^2 I_p \times p) u = [u_1,...,u_n_c] u_i \sim N(\mu_0, \sigma^2_u 1

JonasWallin/PolyMixed documentation built on April 8, 2023, 4:26 p.m.