hugeKmb: Internal wrapper function to implement rank-based correlation...

In GraceYoon/SPRING: Semi-Parametric Rank-based approach for INference in Graphical model (SPRING)

Internal wrapper function to implement rank-based correlation to huge.mb function in "huge" package.

Description

Internal wrapper function to implement rank-based correlation to huge.mb function in "huge" package.

Usage

hugeKmb(
  data,
  lambda,
  type = "trunc",
  sym = "or",
  verbose = TRUE,
  verboseR = TRUE,
  Rmethod = "approx",
  tol = 1e-06
)

Arguments

data	n by p matrix data. usually through pulsar, data will receive subsamples.
lambda	a vector of lambda values
type	a type of variables. "trunc" is default.
sym	"or" is the symmetrizing rule of the output graphs. If sym = "and", the edge between node i and node j is selected ONLY when both node i and node j are selected as neighbors for each other. If sym = "or", the edge is selected when either node i or node j is selected as the neighbor for each other. The default value is "or". (refer to huge manual)
verbose	If verbose = FALSE, tracing information printing for HUGE (High-dimensional Undirected Graph Estimation) with a specified method (currently "mb" is only available) is disabled. The default value is TRUE.
verboseR	If verboseR = FALSE, printing information whetehr nearPD is used or not is disabled. The defalut value is TRUE.
Rmethod	The calculation method of latent correlation. Either "original" method or "approx". If Rmethod = "approx", multilinear approximation method is used, which is much faster than the original method. If Rmethod = "original", optimization of the bridge inverse function is used. The default is "approx".
tol	Desired accuracy when calculating the solution of bridge function in estimateR function.

Value

hugeKmb returns a data.frame containing

• beta:

• path: a list of

• df:

GraceYoon/SPRING documentation built on June 29, 2022, 4:14 p.m.