Package index • defm

All functions
`new_defm_cpp()` `init_defm()` `print_stats()` `nterms_defm()` `nrow_defm()` `ncol_defm_y()` `ncol_defm_x()` `nobs_defm()` `morder_defm()` `new_defm()`	Discrete Exponential Family Model (DEFM)
`get_Y_names()` `get_X_names()`	Access to the names of a model's datasets
`show(<defm_mle>)` `summary(<defm_mle>)` `show(<summary.defm_mle>)`	Fitted DEFM
`logodds()` `defm_mle()` `texreg_fancy()`	Maximum Likelihood Estimation of DEFM
`td_ones()` `td_generic()` `td_formula()` `td_logit_intercept()` `rule_not_one_to_zero()` `rule_constrain_support()` `+`(<DEFM>)	Model specification for DEFM
`get_counters()` `[`(<DEFM_counters>) `set_counter_info()` `length(<DEFM_counters>)` `as.list(<DEFM_counters>)` `as.list(<DEFM_counter>)` `set_counters_names()`	Extract the counters from a DEFM model
`get_stats()`	Get sufficient statistics counts
`loglike_defm()`	Log-Likelihood of DEFM
`loglike_defm_grad()` `loglike_defm_hess()`	Gradient and Hessian of the DEFM log-likelihood
`motif_census()`	Motif census
`sim_defm()`	Simulate data using a DEFM
`summary_table()` `format(<defm_summary_table>)` `print(<defm_summary_table>)` `as.data.frame(<defm_summary_table>)`	Summary table of a fitted DEFM
`valentesns`	Valente's SNS data

Reference