rnetInput: An S4 class for accepting input data common for generating...
In WJL-NCSU/Rnets: Resistance Relationship Networks using Graphical LASSO
Description
See "L1_selection" documentation for more information.
Slots
RawDataA 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_set_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.
DataA dataframe containing the dataset
L1_seta numeric vector containing the candidate L1 penalties
BThe number of subsamples to draw from the data to evaluate topologic stability
B_methodAssigned either "proportionate" or "Total number" depending on how subsample size is determined.
B_setsA matrix (n_B x B) containing the rownumbers of the subsamples
Data_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.
Edge_stabilityA dataframe showing edge stability over the set of generated networks.
StARS_DA vector of D_b values used for L1 selection.
WJL-NCSU/Rnets documentation built on May 31, 2021, 3:11 p.m.
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Description
See "L1_selection" documentation for more information.
Slots
RawDataA 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_set_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.
DataA dataframe containing the dataset
L1_seta numeric vector containing the candidate L1 penalties
BThe number of subsamples to draw from the data to evaluate topologic stability
B_methodAssigned either "proportionate" or "Total number" depending on how subsample size is determined.
B_setsA matrix (n_B x B) containing the rownumbers of the subsamples
Data_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.
Edge_stabilityA dataframe showing edge stability over the set of generated networks.
StARS_DA vector of D_b values used for L1 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.
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