Haar-wavelet spike-and-slab BayesThresh estimator (Abramovich 1998).

Usage

morie_ghosal_wavelet_prior(x, pi = 0.5, sigma = NULL, noise = NULL)

Arguments

x: Numeric data vector.
pi: Numeric prior inclusion probability (default 0.5).
sigma: Optional slab sd.
noise: Optional noise sd.

Value

Named list with estimate, fitted, noise, sigma, inclusion, n, method.

Examples

morie_ghosal_wavelet_prior(x = rnorm(50))
#> $estimate
#> [1] -0.0181759
#> 
#> $fitted
#>  [1] -0.01817534 -0.01817627 -0.01817573 -0.01817603 -0.01817573 -0.01817525
#>  [7] -0.01817529 -0.01817601 -0.01817675 -0.01817495 -0.01817564 -0.01817568
#> [13] -0.01817589 -0.01817570 -0.01817595 -0.01817573 -0.01817604 -0.01817641
#> [19] -0.01817552 -0.01817532 -0.01817601 -0.01817636 -0.01817565 -0.01817591
#> [25] -0.01817654 -0.01817589 -0.01817613 -0.01817602 -0.01817633 -0.01817521
#> [31] -0.01817601 -0.01817650 -0.01817582 -0.01817579 -0.01817626 -0.01817698
#> [37] -0.01817613 -0.01817567 -0.01817591 -0.01817593 -0.01817568 -0.01817634
#> [43] -0.01817548 -0.01817589 -0.01817562 -0.01817550 -0.01817581 -0.01817622
#> [49] -0.01817545 -0.01817665
#> 
#> $noise
#> [1] 1.150162
#> 
#> $sigma
#> [1] 0.001
#> 
#> $inclusion
#> [1] 0.5
#> 
#> $n
#> [1] 50
#> 
#> $method
#> [1] "Haar-wavelet spike-and-slab BayesThresh"
#>