# A function to automatically generate hysteresis plots for all structural parameter estimates.

### Description

Hysteresis plots were introduced by: Snijders, Tom AB, et al. "New specifications for exponential random graph models." Sociological methodology 36.1 (2006): 99-153. They can tell the user about sensitivity of the parameter estimates and whether they should worry about degeneracy.

### Usage

1 2 3 4 5 |

### Arguments

`GERGM_Object` |
A GERGM object returned by the gergm() estimation function. |

`networks_to_simulate` |
Number of simulations per unique parameter value used in the hysteresis plots. Default is 1000. |

`burnin` |
Number of samples from the MCMC simulation procedure that will be discarded before drawing the samples used for hysteresis plots. Default is 500. |

`range` |
The magnitude of the interval over which theta parameter values will be varried for the hysteresis plots. The actual range will be vary from a minimum of theta_value - range * theta_std_error to a maximum of theta_value + range * theta_std_error so the actual parameter ranges will be scaled to the magnitude of the parameter estimate standard errors. Defaults to 4. |

`steps` |
The number of theta values to simulate above and below the estimated theta value within the given range. The total number of simulations is then = 2 * steps + 1. Defaults to 20. |

`initial_density` |
The initial network density used in simulations, can range from 0 to 1. Defaults to 0.2. |

`simulation_method` |
Simulation method for MCMC estimation. Default is "Gibbs" but can also be set to "Metropolis". |

`proposal_variance` |
The variance specified for the Metropolis Hastings simulation method. This parameter is inversely proportional to the average acceptance rate of the M-H sampler and should be adjusted so that the average acceptance rate is approximately 0.25. Default is 0.1. |

`seed` |
Seed used for reproducibility. Default is 123. |

`thin` |
The proportion of samples that are kept from each simulation. For example, thin = 1/200 will keep every 200th network in the overall simulated sample. Default is 1. |

`output_directory` |
The directory where you would like output generated by this function to be saved. If NULL, then the current working directory will be used. Defaults to NULL. |

`output_name` |
The common name stem you would like to assign to all plots generated by this function. If NULL, then no output will be saved to pdf and plots will only be plotted to the graphics device. |

`parallel` |
Logical indicating whether hysteresis plots for each theta parameter should be simulated in parallel. Can greatly reduce runtime, but the computer must have atleast as many cores as theta parameters. Defauts to FALSE. |

### Value

A list object containing network densities for simulated networks.

### Examples

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | ```
## Not run:
set.seed(12345)
net <- matrix(rnorm(100,0,20),10,10)
colnames(net) <- rownames(net) <- letters[1:10]
formula <- net ~ mutual + ttriads
test <- gergm(formula,
normalization_type = "division",
network_is_directed = TRUE,
use_MPLE_only = FALSE,
estimation_method = "Metropolis",
number_of_networks_to_simulate = 40000,
thin = 1/10,
proposal_variance = 0.5,
downweight_statistics_together = TRUE,
MCMC_burnin = 10000,
seed = 456,
convergence_tolerance = 0.01,
MPLE_gain_factor = 0,
force_x_theta_updates = 4)
hysteresis_results <- hysteresis(
test,
networks_to_simulate = 1000,
burnin = 500,
range = 2,
steps = 20,
simulation_method = "Metropolis",
proposal_variance = 0.5)
## End(Not run)
``` |

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