rnetInput: An S4 class for accepting input data common for generating...
In Rnets: Resistance Relationship Networks using Graphical LASSO
Description
See "L1_selection" documentation for more information.
Slots
raw_dataA dataframe containing the original dataset.
cor_methodThe type of correlation matrix to use. Must be a partial match to one of the following strings: 'pearson', 'spearman', 'kendall'.
cor_pairingMethod for handling how missing data is handled in pairs. See 'pair' argument in function 'cor' for more information.
n_thresholdThe 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_origThe declared L1 penalty to be used when estimating rnet topology
V_origThe declared set of k variables to be included in the rnet as vertices
forced_zerosA matrix with 2 columns containing pairs of vertices to force to be conditionally independent in the rnet
layout_masterA k x 2 matrix x & y coordinates of each vertex in the graph.
xA dataframe containing the dataset
L1_valuesa numeric vector containing the candidate L1 penalties
BThe number of subsamples to draw from the data to evaluate topologic stability
method_bAssigned either "proportionate" or "Total number" depending on how subsample size is determined.
sets_bA matrix (n_B x B) containing the rownumbers of the subsamples
array_bAn arrary (n_b x k x B) containing the data from the B_sets matrix
pr_bThe size of the subsample B as a proportion of the complete dataset
n_bThe size of the subsample
W_aggrAn 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_aggrAn array (k x k x B x L1) containg all the adjacency matrices generated by the all of subsamples over the L1 penalties
MA dataframe with with graphical density data over the set of generated networks.
stabilityA dataframe showing edge stability over the set of generated networks.
DA vector of D_b values used for L1 selection.
D_threshThe suggested maximum D value for selection.
Rnets documentation built on July 23, 2019, 9:04 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description
See "L1_selection" documentation for more information.
Slots
raw_dataA dataframe containing the original dataset.
cor_methodThe type of correlation matrix to use. Must be a partial match to one of the following strings: 'pearson', 'spearman', 'kendall'.
cor_pairingMethod for handling how missing data is handled in pairs. See 'pair' argument in function 'cor' for more information.
n_thresholdThe 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_origThe declared L1 penalty to be used when estimating rnet topology
V_origThe declared set of k variables to be included in the rnet as vertices
forced_zerosA matrix with 2 columns containing pairs of vertices to force to be conditionally independent in the rnet
layout_masterA k x 2 matrix x & y coordinates of each vertex in the graph.
xA dataframe containing the dataset
L1_valuesa numeric vector containing the candidate L1 penalties
BThe number of subsamples to draw from the data to evaluate topologic stability
method_bAssigned either "proportionate" or "Total number" depending on how subsample size is determined.
sets_bA matrix (n_B x B) containing the rownumbers of the subsamples
array_bAn arrary (n_b x k x B) containing the data from the B_sets matrix
pr_bThe size of the subsample B as a proportion of the complete dataset
n_bThe size of the subsample
W_aggrAn 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_aggrAn array (k x k x B x L1) containg all the adjacency matrices generated by the all of subsamples over the L1 penalties
MA dataframe with with graphical density data over the set of generated networks.
stabilityA dataframe showing edge stability over the set of generated networks.
DA vector of D_b values used for L1 selection.
D_threshThe suggested maximum D value for selection.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.