rnetInput: An S4 class for accepting input data common for generating...

Description Slots

Description

See "L1_selection" documentation for more information.

Slots

raw_data

A dataframe containing the original dataset.

cor_method

The type of correlation matrix to use. Must be a partial match to one of the following strings: 'pearson', 'spearman', 'kendall'.

cor_pairing

Method for handling how missing data is handled in pairs. See 'pair' argument in function 'cor' for more information.

n_threshold

The minimum number of valid pair-wise observations that must exist for an edge to be estimated. Vertex pairs with fewer valid pair-wise observations are assumed to be conditiontally independent.

L1_orig

The declared L1 penalty to be used when estimating rnet topology

V_orig

The declared set of k variables to be included in the rnet as vertices

forced_zeros

A matrix with 2 columns containing pairs of vertices to force to be conditionally independent in the rnet

layout_master

A k x 2 matrix x & y coordinates of each vertex in the graph.

x

A dataframe containing the dataset

L1_values

a numeric vector containing the candidate L1 penalties

B

The number of subsamples to draw from the data to evaluate topologic stability

method_b

Assigned either "proportionate" or "Total number" depending on how subsample size is determined.

sets_b

A matrix (n_B x B) containing the rownumbers of the subsamples

array_b

An arrary (n_b x k x B) containing the data from the B_sets matrix

pr_b

The size of the subsample B as a proportion of the complete dataset

n_b

The size of the subsample

W_aggr

An array (k x k x B x L1) containg all the weighted adjacency matrices generated by the all of subsamples over the L1 penalties

A_aggr

An array (k x k x B x L1) containg all the adjacency matrices generated by the all of subsamples over the L1 penalties

M

A dataframe with with graphical density data over the set of generated networks.

stability

A dataframe showing edge stability over the set of generated networks.

D

A vector of D_b values used for L1 selection.

D_thresh

The suggested maximum D value for selection.


Rnets documentation built on July 23, 2019, 9:04 a.m.