SingleSite_regression_sampler_parallel: Draws samples from all "fixed" coefficients (fixed and...

In deruncie/MegaLMM: MegaLMM

Draws samples from all “fixed" coefficients (fixed and random) of a set of parallel linear regression models, conditional on the variance components.

Description

The model is either:

• y_i = X1_base*alpha1 + X1_list_[i]*alpha2 + X2*beta + e, e ~ N(0,1/Y_prec[i]*V)

• y_i = X1_base*alpha1 + X1_list_[i]*alpha2 + X2*V_*beta + e, e ~ N(0,1/Y_prec[i]*V)

Where V = RtR, priors on elements of alpha1, alpha2 and beta are independent. Each column of Y is considered independent

Usage

SingleSite_regression_sampler_parallel(
  Y,
  X1_base,
  X1_list_,
  X2_,
  Vx_,
  h2s_index,
  chol_V_list_,
  Y_prec,
  Y_prec_a0,
  Y_prec_b0,
  prior_prec_alpha1,
  prior_prec_alpha2,
  prior_mean_beta,
  prior_prec_beta,
  current_alpha1s_,
  current_alpha2s_,
  BayesAlphabet_parms
)

Arguments

Y	n x p matrix of observations
X1_base	n x a1 matrix of X1 covariates common to all p. Can be NULL
X1_list_	p-list of n x a2 matrices of X1 covariates unique to each p. Can be NULL
h2s_index	p-vector of indices for to select appropriate V of each trait
chol_V_list_	list of cholesky decompositions of V: RtR (each nxn). Can be either dense or sparse
Y_prec	p-vector of Y current precisions
Y_prec_a0, Y_prec_b0	scalars giving the shape and rate of the Gamma distribution for the prior on Y_prec
prior_prec_alpha1	a1 x p matrix of prior precisions for alpha1
prior_prec_alpha2	p-vector of precision of alpha2s for each trait
prior_mean_beta	b x p matrix of prior means of beta
prior_prec_beta	b x p matrix of prior precisions of beta
which_sampler	int: 1: block sampler: b < n 2: block sampler: n >= b and X doesn't factorize 3: block sampler: n >= b, but X factorizes into UxVx where Ux is n x m and Vx = m x b, and m << n <= b
X2	either X2, a n x b matrix, or Ux, a n x m matrix. If Ux, then V must be non-NULL
V_	m x b matrix if X2 is Ux, otherwise NULL
beta1_list_	p-list of a2-vectors for X1 coefficients. Can be NULL
beta2	a b x p matrix of current values for beta
beta2_alpha_	b x p matrix for BayesC priors for beta2. Can be NULL
beta2_delta_	b x p matrix for BayesC priors for beta2. Can be NULL,
beta2_p_i_	b x p matrix for BayesC priors for beta2. Can be NULL

Value

List with elements:

• alpha1 a1 x p matrix of alpha1

• alpha2 concatenated vector of alpha2 for all traits

• beta b x p matrix of beta

• Y_prec p x 1 vector of Y_prec

• beta2_alpha b x p matrix (optional)

• beta2_delta_ b x p matrix (optional)

deruncie/MegaLMM documentation built on June 10, 2025, 7:26 p.m.