qtl_pheno_simu: Simulating phenotype values with neighbor effects.
In rNeighborGWAS: Testing Neighbor Effects in Marker-Based Regressions

A function to simulate phenotype values with multiple sources of variation controlled

qtl_pheno_simu(
  b_self,
  b_nei,
  eigenK_self,
  eigenK_nei,
  b_ratio = c(1, 1),
  pveB,
  pve
)

`b_self`	A n x 1 genotype vector to design major additive genetic effect.
`b_nei`	A vector of an explanatory variable for neighbor effects
`eigenK_self`	Products of `eigen()` with self covariance matrices that are used as explanatory variables for the phenotype.
`eigenK_nei`	Products of `eigen()` with neighbor covariance matrices that are used as explanatory variables for the phenotype.
`b_ratio`	Ratio for contributions of `eigenK_self` and `eigenK_nei` to the phenotype.
`pveB`	Proportion of variance explained by genetic effects attributable to the fixed effects (i.e., b_.. vector).
`pve`	Proportion of variance explained by all genetic effects (i.e., b_.. and eigenK_..)

A list of simulated phenotypes

y Simulated phenotype values
beta_self major self-genetic effects
beta_nei major neighbor effects
sigma_self self polygenic effects
sigma_nei neighbor polygenic effects
epsilon residuals
res_pveB realized proportion of variation explained by major-effect genes
res_pve realized proportion of variation explained by major-effect genes and polygenic effects