BayesC-pi spike-and-slab variable selection (short Gibbs)

BayesC-pi spike-and-slab variable selection (short Gibbs)

Usage

morie_bayes_cpi_genomic(
  x,
  y,
  n_iter = 300,
  burn = 100,
  pi_init = 0.1,
  seed = 0,
  deterministic_seed = NULL
)

Arguments

x

(n x p) marker matrix.

y

Numeric response.

n_iter

Iterations.

burn

Burn-in.

pi_init

Initial inclusion probability.

seed

Seed.

deterministic_seed

Optional integer; if supplied, RNG state is derived via morie_det_rng() keyed on ("bglup", deterministic_seed) so Py<->R streams agree on the canonical fixture. When NULL (default) behaviour is unchanged.

Value

list(estimate, beta, beta_pip, pi, sigma_b2, sigma2, n_iter, n, p, method).

References

Habier-Fernando-Kizilkaya-Garrick (2011); Montesinos Lopez Ch 4.

Examples

morie_bayes_cpi_genomic(x = rnorm(50), y = rnorm(50))
#> $estimate
#> [1] 0.03935286
#> 
#> $beta
#> [1] 0.03935286
#> 
#> $beta_pip
#> [1] 0.29
#> 
#> $pi
#> [1] 0.4193751
#> 
#> $sigma_b2
#> [1] 0.5130478
#> 
#> $sigma2
#> [1] 0.7295735
#> 
#> $intercept
#> [1] 0.02140593
#> 
#> $n_iter
#> [1] 200
#> 
#> $n
#> [1] 50
#> 
#> $p
#> [1] 1
#> 
#> $method
#> [1] "BayesC-pi short Gibbs"
#>