BLiP_cts: BLiP when the set of locations is continuous, e.g., when...

In amspector100/blipr: A Bayesian Linear Program for resolution-adaptive signal detection

BLiP when the set of locations is continuous, e.g., when working with image data.

Description

BLiP when the set of locations is continuous, e.g., when working with image data.

Usage

BLiP_cts(
  locs,
  grid_sizes = DEFAULT_GRID_SIZES,
  weight_fn = inverse_radius,
  extra_centers = NULL,
  max_pep = 0.25,
  shape = "circle",
  min_blip_size = 5000,
  verbose = T,
  ...
)

Arguments

locs	A (N, num_disc, d)-dimensional array. Here, N is the number of samples from the posterior, d is the number of dimensions of the space, and each point corresponds to a signal in a particular posterior sample.
grid_sizes	List of grid sizes to split up the locations. The grid size is inversely proportional to the distance between lattice points.
weight_fn	Weight function which maps candidate groups to weights. Defaults to inverse radius.
extra_centers	An (ncenters, d)-dimensional matrix. At each resolution, candidate groups will be computed with centers at this location.
max_pep	The maximum allowable PEP for output candidate groups. Defaults to 0.25.
shape	One of ('circle', 'square').
min_blip_size	Combines connected components so all subproblems are at least this size.
verbose	If T, gives occasional status updates. Defaults to T.
...	Other arguments to the underlying BliP call, such as the error rate or nominal level.

amspector100/blipr documentation built on June 22, 2022, 2:43 a.m.