Man pages for samthiriot/gosp.dpp
Pairing of entities to generate structured synthetic populations
| add_linebreaks_attributes | Adds line breaks to forge axes labels |
| as.data.frame.dpp_degree_cpt | Coerce a distribution of degrees into a data frame |
| as.data.frame.dpp_matching_probas | Coerce pairing probabilities into a data frame |
| as.data.frame.dpp_sample | Coerce the a dpp sample into a data frame |
| as.igraph.dpp_population | Exports a population as an igraph graph. |
| as.igraph.dpp_result | Exports a generation result as an igraph graph. |
| as.latex.relaxation.constrainsts | Writes relaxation parameters as LaTeX |
| as.latex.table.discrete | Creates a LaTeX view with the discrete values |
| as.latex.table.probabilistic.init | Creates a LaTeX view with the probabilistic values after... |
| as.latex.table.probabilistic.solved | Creates a LaTeX view with the probabilistic values after... |
| as.merged.dataframe | Exports a synthetic population as one unique dataframe |
| assert.equal | Asserts two values are equal. |
| assert.hypothesis | Asserts a given hypothesis on a given solution for a given... |
| assess.max.pd | Computes the maximum degree which might be obtained using a... |
| best.solution | Selects one best solution among a list of possible solutions |
| chisq.test.or.NA | Quantifies the chi2 goodness of fit between two dataframes |
| compute_average_degree | Computes the average degree from a distribution of degrees |
| compute_common_columns | Identifies the columns present it two datasets |
| create_degree_probabilities_table | Creates a table storing probabilities for degrees |
| create_matching_probabilities_table | Creates a table storing matching probabilities |
| create_sample | Creates a sample organized for dpp manipulation. |
| detect.missing.chains | Detects the missing chains of variables |
| detect.problems | Checks the consistency of a solution |
| dwellings_households | Example dataset for DPP with simple dwellings and households |
| ensure.form | Ensures the content of a solution is in the expect format |
| ensure_presence_ggplot | Stops if ggplot2 is not installed |
| errors.pdi | Measure the errors in the distributions of degrees pdi |
| errors.pdj | Measure the errors in the distributions of degrees pdj |
| errors.pij | Measure the errors in the pairing probabilities pij |
| expand_with_variable_col.data.frame | Expands a data frame by adding combinations with a novel... |
| expand_with_variable.dpp_degree_cpt | Expands a conditional probability table for degrees with an... |
| expand_with_variable.dpp_matching_probas.A | Expands the columns of matching probabilities with additional... |
| expand_with_variable.dpp_matching_probas.B | Expands the rows of matching probabilitis with additional... |
| expand_with_variable_row.data.frame | Expands a data frame by adding combinations with a novel... |
| expand_with_variables.dpp_degree_cpt | Expands a conditional probability table for degrees with... |
| expand_with_variables.dpp_matching_probas.A | Expands the columns of matching probabilities with additional... |
| expand_with_variables.dpp_matching_probas.B | Expands the rows of matching probabilities with additional... |
| extract_attributes_values | Extracts attribute values from a string |
| first.columns | Returns the first n columns of a dataframe and adds ... |
| first.lines | Returns the first n rows of a dataframe and adds ... |
| fisher.pvalue.or.NA | Quantifies the Fisher goodness of fit between two dataframes |
| generate.hypothesis | generates the hypothesis to explore a given solution |
| gof.freeman_tukey | Quantifies the goodness of fit between two dataframes |
| heat_map_gradient | Creates a ggplot2 gradient adapted to the values for an... |
| inf_to_zeros | Replaces Infinite by zeros |
| ipf.2d | Applies Iterative Proportional Fitting on a 2d dataframe |
| ipf.2d.stackoverflow | A simple Iterated Proportional Fitting implementation |
| list_variabes_modalities | Extracts the list of modalities per variable |
| matching.fix | Fix inputs parameters for DPP resolution |
| matching.generate | Generates a synthetic population based on the resolution of... |
| matching.generate.add_degree | Adds a target degree column to a population based on the... |
| matching.generate.resize_population | Takes an original sample, and returns 'count.required'... |
| matching.prepare | Prepares a case for Direct Probabilistic Peering |
| matching.solve | Solves the equations by arbitrating. |
| mean.data.frame | Computes the mean of all the values inside a dataframe |
| measure_contigencies | Measures the contigencies from a sample |
| measure_pairing_from_df | Create pairing probabilities |
| merge_links | Merge entities and attributes |
| name.hypothesis | A string representing an hypothesis |
| nan_to_zeros | Replaces NaN by zeros |
| normalise | Normalise an object |
| paste.known | Concatenates the known values |
| plot_average_degree_A | Plots average degrees, expected and generated, as bar charts |
| plot.dpp_resolved | Plots a visual synthese of the errors induced by the... |
| plot_errors | Plots the error measures |
| plot_errors_pdi | Plots expected and generated probability distribution of... |
| plot_errors_pij | Plots expected and generated pairing probability |
| plot_frequencies_A | Plots expected and generated frequencies |
| plot_population_sizes | Plots the expected and generated population sizes |
| plot_relaxation | Plots the relaxation parameters |
| plot_variable | Plots the difference between proportions in the original... |
| print.dpp_degree_cpt | Display a sample for Direct Probabilistic Peering |
| print.dpp_matching_probas | Display matching probabilities |
| print.dpp_measure | Display the result of measures on a generated population |
| print.dpp_population | Display a generated population |
| print.dpp_prepared | Display a prepared case |
| print.dpp_resolved | Display the result of a resolution |
| print.dpp_result | Display a generated population |
| print.dpp_sample | Display a sample for Direct Probabilistic Peering |
| propagate.direct | Completes a partial solution by inference |
| quantify.errors | Quantifies the errors of a solution |
| rectify.degree.counts | Patches a degree distribution contingencies so its totals fit... |
| relax.zeros | Relax the dataset by changing zeros with low probability |
| remove_excess_probas_pd | Removes useless modalities from a probability distribution |
| remove_excess_probas_pd_lines | Removes useless modalities from a probability distribution |
| reorder_column_modalities | Reorders the modalities inside columns of a dataset |
| reorder_columns | Reorders the columns of a dataset so they are in the expected... |
| resolve | Resolves a partial solution by inference and hypothesis |
| resolve.missing.chain | Solves a chain of missing variables |
| round_sum | Rounds an object by ensuring its totals remains equal before... |
| set.rownames.degrees | Sets row names for degrees distribution |
| sum.list | Sums applied on a list |
| underscore_to_varmod | Replace underscores by variables and modalities |
| update_degree_distribution | Update a given distribution of degrees probabilities so its... |
| update_degree_distribution.col | Update a given distribution column of degrees probabilities... |
