Network probit with fixed effects

add_predict | add predicted values or residuals under FE projection |

add_xtilde | add xtilde's by reference |

add_ystar | Add latent index to dataset for given structural parameters. |

center | Center a vector |

compute_H | Compute H for ij link (definition see paper) |

compute_J | Compute J (see paper for definition) |

compute_omega | Compute omega for ij link (definition see paper) |

compute_p | Compute linking probability p for ij link (definition see... |

compute_p1 | Compute p(1 - p) for ij link (definition see paper) |

compute_r | Compute probability of reciprocated link |

compute_ystar | Compute ystar |

copy_ij_value_to_ji | Make new variables that for entry i,j contains the j,i values... |

copy_var_to_new_suffix | Copy variable, new name changes the suffix |

define_model | Define a network model |

define_sim_design_jochmans | Define a simulation design (Jochmans) |

double_bootstrap | Double bootstrap procedure |

double_bootstrap_inner | Fast computation of bootstrap bias |

draw_bootstrap_sample | Draw from bootstrap distribution |

draw_j18_dynamic_meeting | Sample from alternative with dynacmic behavior |

draw_network_jochmans_2018 | Sample a random network following modified Jochmans design |

excess_trans | compute observed excess transitivity |

fast_excess_transitivity | Compute excess transitivity |

identity | Return vector unchanged |

long_to_wide | Reshape dyadic network data from long (ij, i != j) to wide... |

MLE_stage1 | ML estimation of stage 1 |

MLE_stage2 | ML estimation stage 2 |

MLE_stage2_gradient | Stage 2: solve likelihood directly |

MLE_stage2_mle | Stage 2: solve likelihood directly |

netprobitFE | netprobitFE |

num_in_triangles | Detect number of triangles that this link is a part of |

num_pairs | compute number of (ordered) pairs from 1, ..., N |

num_trans_closures | Detect number of transitive relationships closed by this link |

partial_J_ystar1 | Compute derivative of J (see paper) wrt ystar1 |

partial_p_ystar | Compute derivative of p (linking probability) wrt to ystar |

partial_p_ystar_ystar | Compute 2nd order derivative of p (linking probability) wrt... |

partial_r_rho | Compute derivative of r wrt rho (see paper for definition) |

partial_r_ystar1 | Compute derivative of r wrt rho |

partial_r_ystar1_rho | Compute 2nd order derivative of r wrt ystar1 and rho |

partial_r_ystar1_ystar1 | Compute 2nd order derivative of r wrt ystar1 and ystar1 |

partial_r_ystar1_ystar2 | Compute 2nd order derivative of r wrt ystar1 and ystar2 |

read_link_data | use C++ class LinkVariable to establish link to R data frame |

simulate_methods | Run simulations |

triangles_biascorr_new_vars | add new link variables that are required for bias correction |

triangle_test | Compute specification test based on transitive triangles |

ttest_rho | Compute bias adjusted t-statistic for parameter rho |

ttest_theta | Compute bias adjusted t-statistic for parameter theta |

weighted_inner_prod | Compute a weighted inner product |

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.