L1Selection: L1 Selection for Rnets

In EpidemiologyDVM/duke-rnet-quick: Resistance Relationship Networks using Graphical LASSO

Description

An implementation of the Stability Approach to Regularization Selection (StARS) method for L1 penalty selection for use with Rnets method.

Usage

L1Selection(
  x,
  L1_values,
  B = 100,
  n_b = 0.5,
  vertices = NULL,
  n_min = 1,
  cor_method = "s",
  cor_pairing = "pair",
  forced_zeros = NULL,
  subset = NULL,
  D_thresh = 0.05,
  verbose = TRUE
)

Arguments

x	The dataset containing the MICs
L1_values	The set of candidate L1 penalties to be evaluated for creating a sparse precision matrix. Must be non-negative.
B	The number of subsamples to evaluate network stability. Defaults to 100 subsamples.
n_b	The size of the subsample to be drawn from the data. If 0 < n_b < 1, this is interpreted as a proportion of the data set; if n_b > 1, it is interpreted as a set sample size. Defaults to 50% of sample size.
vertices	A character vector corresponding to the names of the antibiotics to include in the Rnet. Defaults to an empty list, in which case all columns in 'MIC_data' will be included in the Rnet
n_min	The minimum number of observations required for an an estimated correlation to be valid. Defaults to 0, in which case any number of observations will be sufficient to estimate a valid correlation
cor_method	The method used to estimate the correlation matrix. Must be 'pearson', 'spearman', or 'kendall'. Partial matches allowed. Defaults to 'spearman'.
cor_pairing	The method used to determine how NAs are handled when determining which pairs are used to estimate correlations. See 'cor' function documentation for additional information.
forced_zeros	Edges to be omitted from the Rnet.
subset	The rule for stratifying the data, if desired.
D_thresh	Maximum tolerated D value. Suggested D_thresh = 0.05.
verbose	Logical that tells the function to list progress in estimating Rnets from subsets.

Value

A vector of D statistics, corresponding the tested L1 values.

Examples

 ABX_LIST <- c('AMP', 'AMC', 'AXO', 'TIO', 'NAL', 'CIP', 'STR', 'GEN', 'COT', 'FIS')

 EC_all_L1Selection <- L1Selection(
                             x = NARMS_EC_DATA, 
                             L1_values = seq(0.05, 0.50, 0.05),
                             n_b = 1500,
                             vert = ABX_LIST
                             )
print(EC_all_L1Selection)

EpidemiologyDVM/duke-rnet-quick documentation built on Dec. 17, 2021, 7:20 p.m.