R: Generative Mechanism Estimation in Temporal Complex Networks

# Generative Mechanism Estimation in Temporal Complex Networks

## Documentation for package ‘PAFit’ version 1.2.11

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS

## Help Pages

PAFit-package | Generative Mechanism Estimation in Temporal Complex Networks
as.PAFit_net | Converting an edgelist matrix to a PAFit_net object
coauthor.author_id | A collaboration network between authors of papers in the field of complex networks with article time-stamps
coauthor.net | A collaboration network between authors of papers in the field of complex networks with article time-stamps
coauthor.truetime | A collaboration network between authors of papers in the field of complex networks with article time-stamps
ComplexNetCoauthor | A collaboration network between authors of papers in the field of complex networks with article time-stamps
from_igraph | Convert an igraph object to a PAFit_net object
from_networkDynamic | Convert a networkDynamic object to a PAFit_net object
generate_BA | Simulating networks from the generalized Barabasi-Albert model
generate_BB | Simulating networks from the Bianconi-Barabasi model
generate_ER | Simulating networks from the Erdos-Renyi model
generate_fit_only | Simulating networks from the Caldarelli model
generate_net | Simulating networks from preferential attachment and fitness mechanisms
generate_simulated_data_from_estimated_model | Generating simulated data from a fitted model
get_statistics | Getting summarized statistics from input data
graph_from_file | Read file to a PAFit_net object
graph_to_file | Write the graph in a PAFit_net object to file
Jeong | Jeong's method for estimating the preferential attachment function
joint_estimate | Joint inference of attachment function and node fitnesses
Newman | Corrected Newman's method for estimating the preferential attachment function
only_A_estimate | Estimating the attachment function in isolation by PAFit method
only_F_estimate | Estimating node fitnesses in isolation
PAFit | Generative Mechanism Estimation in Temporal Complex Networks
PAFit_data | Getting summarized statistics from input data
PAFit_oneshot | Estimating the nonparametric preferential attachment function from one single snapshot.
plot.Full_PAFit_result | Plotting the estimated attachment function and node fitness
plot.PAFit_net | Plot a 'PAFit_net' object
plot.PAFit_result | Plotting the estimated attachment function and node fitness of a 'PAFit_result' object
plot.PA_result | Plotting the estimated attachment function
plot_contribution | Plotting contributions calculated from the observed data and contributions calculated from simulated data
print.CV_Data | Printing simple information of the cross-validation data
print.CV_Result | Printing simple information of the cross-validation result
print.Full_PAFit_result | printing information on the estimation result
print.PAFit_data | Printing simple information on the statistics of the network stored in a 'PAFit_data' object
print.PAFit_net | Printing simple information of a 'PAFit_net' object
print.PAFit_result | printing information on the estimation result stored in a 'PAFit_result' object
print.PA_result | Printing information of the estimated attachment function
summary.CV_Data | Printing summary information of the cross-validation data
summary.CV_Result | Output summary information of the cross-validation result
summary.Full_PAFit_result | Summary information on the estimation result
summary.PAFit_data | Output summary information on the statistics of the network stored in a 'PAFit_data' object
summary.PAFit_net | Summary information of a 'PAFit_net' object
summary.PAFit_result | Output summary information on the estimation result stored in a 'PAFit_result' object
summary.PA_result | Summary of the estimated attachment function
test_linear_PA | Fitting various distributions to a degree vector
to_igraph | Convert a PAFit_net object to an igraph object
to_networkDynamic | Convert a PAFit_net object to a networkDynamic object