Man pages for ANTs
Animal Network Toolkit Software
| ant | ANT diagnostic for permuted statistics |
| assoc.gfi | Generalized affiliation index |
| assoc.indices | Association indices |
| assoc_mat | Association indexes |
| assoc_mat_full | Association indexes |
| assoc_mat_one_id | Association indexes for one individual |
| check.df | Data frame ANT check |
| check.id | Data frame ANT ID check |
| check.mat | Matrix ANT check |
| convert.socprog | Converts Socprog data frame |
| df.col.findId | Finds a data frame index |
| df.create | Creates an empty data frame or a list of empty data frames |
| df.create.single | Creates an empty data frame. |
| df.ctrlFactor | Creates a column that merges multiple columns |
| df_merge | Merge two data frames |
| df_to_gbi | Group by individual matrix. |
| df.to.gbi | Data frame to GBI. |
| df.to.gbi.focal | Converts a data frame of individual associations into a group... |
| df.to.mat | Data frame to a matrix |
| edgl.to.grp | Dyadic data frame (edge list) to linear group by individual... |
| edgl_to_matrix | Edge list to matrix |
| error_matrix | Errors related to matrices |
| gbi_createEmpty | Empty group by individual matrix |
| gbi.to.df | Group by individual matrix to linear data frame of... |
| grp.to.edgl | Linear group by individual data frame to dyadic data frame... |
| import.df | Imports data frames |
| import.mat | Imports matrices |
| laplacian_energy_degrees | Laplacian energy. |
| ldf_merge | Merge list of data frames |
| listDf_merge_single_column | Merge columns of a List of data frames. |
| list_lapply | Lapply function |
| list_to_df | List to data frame. |
| mat_binaryzation | Matrix binarization. |
| mat.binaryzation | Matrix binarization. |
| mat_cols_sums | From Column Sums. |
| mat_col_sumsBinary | Binary version of column sum. |
| mat_dim | Dimensions of a matrix |
| mat_filter | Matrix filtering |
| mat_find0 | Find zeros in a Matrix. |
| mat_isSquare | Is square. |
| mat.lp | Laplacian matrix |
| mat_row_extract | Extract matrix row. |
| mat_rows_sums | From row Sums. |
| mat_rows_sumsBinary | Binary version of row sum. |
| mat.symetrize | Symmetrizes matrix |
| mat.to.edgl | Matrix to edge list |
| mat.vectorization | Matrix vectorization |
| merge.met | Merge data frame with metric |
| met.affinity | Affinity |
| met.affinity.single | Affinity |
| met.all | All node metrics |
| met.alterDegree | Alters sum or average of met.degree or met.strength. |
| met.assortativity | Assortativity |
| met.assortativityCat | Assortativity |
| met.assortatvityContinuous | Continuous assortativity |
| met.betweenness | Betweenness centrality |
| met.betweenness.single | Betweenness centrality |
| met.cc | Binary global clustering coefficient |
| met.ci | Centralisation index |
| met.ci.single | Centralisation index |
| met.coutTriangles | Calculates the number of triangles in a network |
| met.degree | Degree |
| met.degree.single | Degree on single matrix |
| met.density | Density |
| met.dge.single | Average Dyadic Efficiency |
| met.diameter | Diameter |
| met.disparity | Disparity |
| met.disparity.single | Disparity |
| met.eigen | Eigenvector Centrality |
| met.eigen.single | Eigenvector Centrality |
| met.ge | Global efficiency |
| met.geodesic | Geodesic distances |
| met.geodesicDiameter.single | Geodesic distances and diameter |
| met.ge.single | Global efficiency |
| met.indegree | Indegree |
| met.indegree.single | Indegree |
| met.instrength | Instrength |
| met.instrength.single | Instrength |
| met.lp | Laplacian centrality |
| met.lpcB | Binary symetric Laplacian centrality |
| met.lpcentEvcent | Laplacian centrality |
| met.lpcW | Wheigthed symetric Laplacian centrality |
| met.lpEnergyEigen | Laplacian energy. |
| met.lp.single | Symetric Laplacian centrality |
| met.outdegree | Outdegree |
| met.outdegree.single | Outdegree |
| met.outstrength | Outstrength |
| met.outstrength.single | Outstrength |
| met.reach | Reach centrality |
| met.reach.single | Reach centrality |
| met.ri | R-Index |
| met.ri.single | R-Index |
| met_strength | strength |
| met.strength | Strength |
| met.strength.single | Strength |
| perm_dataStream1 | Data Stream gambit of the group Permutations without control... |
| perm_dataStream1_focal | Data Stream gambit of the group Permutations without control... |
| perm_dataStream_ControlFactor | Data Stream gambit of the group Permutations with control... |
| perm.dataStream.focal | Converts a data frame of individual associations into a group... |
| perm.dataStream.group | Data stream permutation for association data |
| perm.double.focal | Data stream permutation for focal sampling data . |
| perm.double.focal.single | Double permutation approach for focal sampling |
| perm.double.grp | Data stream permutation for association data |
| perm.double.grp.single | Double permutation approach for gambit of the group |
| perm.ds.focal | Data stream permutation for focal sampling data . |
| perm.ds.grp | Data stream permutation for association data |
| perm.edgl | Edge list link permutations on an edgelist |
| perm_matVec | Vectorize matrix permutation |
| perm.met.degree.single | Link perm keeping structure on a single matrix |
| perm.net.degree | Link permutation keeping the structure |
| perm.net.links.single | Matrix edge permutations |
| perm.net.lk | Matrix links permutations |
| perm.net.lk.w | Links weigths permutations |
| perm.net.nl | Node label permutations with or without random factor(s) |
| perm.net.nl.str | Nodes labels permutation keeping network structure |
| perm.net.nl.str.single | Nodes labels permutation keeping network structure |
| perm_net_weigths | Edgelist weigths permutations |
| perm.net.weigths | Network weigths permutation |
| perm_nl_rf | Node lable permutation with random factors |
| perm.nodeLabel | Node label permutations |
| perm_nodeLabels | Node label permutations. |
| perm.redo | Repeats a permutation according to random factors |
| perm_vec_factor | Permute factor vector. |
| perm_vec_int | Vector permutations. |
| post.dist | Histogram of posterior distribution |
| redo.ds.focal.cum | Function for cumulative permutations for symmetric behaviour... |
| redo.ds.focal.glm | Focal Data stream Recursive function for error found in... |
| redo.ds.focal.glmm | Focal Data stream Recursive function for error found in... |
| redo.ds.focal.lm | Focal Data stream Recursive function for error found in... |
| redo.ds.grp | gambit of the group data stream function for error found in... |
| redo_perm_dataStream_1 | Data Stream gambit of the group cumulative permutations... |
| redo_perm_dataStream1_focal | Data Stream gambit of the group Permutations without control... |
| redo_perm_dataStream_ControlFactor | Data Stream gambit of the group cumulative permutations with... |
| redo_perm_dataStream_ControlFactor_scd | Data Stream gambit of the group cumulative permutations with... |
| redo_perm_dataStream_focal | Data Stream Focal Sampling cumulative permutations without... |
| redo.perm.ds.grp.cum | Function for cumulative permutations on a data frame of... |
| redo.perm.ds.grp.cum.scd | cumulative permutations on GBI or GBI with control factors |
| sampling.effort | Sampling effort |
| sampling.robustness | Metric robustness |
| sampling.uncertainty | Metric uncertainty |
| sim.df | Simulated data frame |
| sim.focal.directed | Focal sampling directed data |
| sim.focal.undirected | Focal sampling undirected data |
| sim.gbi | Group by individual (GBI) matrix |
| sim.gbi.att | Dyadic attributes for sim.gbi data |
| sim.grp | Simulated data collected through gambit of the group sampling |
| sim.m | Simulated Matrix of interactions |
| sim.socprog | Simulated Socprog data format |
| stat.ci | Confidence interval |
| stat.cor | Correlation test on permuted data. |
| stat.deletions | Network target & random deletion simulations |
| stat.deletionsPlot | Plot for network deletion simulations |
| stat.glm | Permuted Generalized Linear Model |
| stat.glmm | Extracts statistical measures of interest in Generalized... |
| stat.glmm.no.first.model | Extracts statistical measures of interest in Generalized... |
| stat.glmm.parallel | Extracts statistical measures of interest in Generalized... |
| stat.lm | Extracts statistical measures of interest in Linear Model |
| stat.model.diag | Diagnostic plot for lm, glm, lmer,glmer models |
| stat.p | P-value |
| stat.t | T-test on data frame |
| stat.tauKr | Matrix TauKr correlations |
| stat.tauKrPartial | Partial matrix TauKr correlations |
| stat.tauKrPartialPermSig | Partial matrix TauKr correlations |
| stat.tauKrPermSig | Matrix TauKr correlations |
| stat.tauKrSimple | Matrix TauKr correlations |
| tauSD | TauKr standard deviation |
| time.heterogeneity | Create a matrix of time of observation per dyades |
| tobs_to_mat | Control heterogeneity of time of observation |
| vec_char_as_factor | As factor |
| vec_char_extract_IdValue | Extract vector elements |
| vec_fill | Merge |
| vec_intersect | intersect |
| vec_levels | Uniques |
| vec_lowertri_to_mat | Vector to matrix lower triangle |
| vec_num_extract_IdValue | Extract ID |
| vec_sample | Vector sample |
| vec_sum | Sum |
| vec_to_mat | Vector to matrix |
| vec_to_mat_add_diag | Vector to matrix and adding diag |
| vec_unique | Vector uniques |
| vec_vec_multiply | Vectors multiply |
| vec_vec_sum | Vectors multiply |
| vis.post.distribution | Histogram of posterior distribution |
| vis.post.distribution2 | Histogram of posterior distribution |
| which_equal | Equal |
| which.metric | Which metric to choose |
| which.protocol | Which metric to choose |
