spatialSAOM: Spatial Stochastic Actor-Oriented Model

Description Usage Arguments Value Author(s) References

View source: R/spatialSAOM.R

Description

Fit a SAOM regression model based on a static, structural network and a set of covariates. The typical application is a diffusion model, where the network is defined by geographic adjacency, and the dependent variable is binary or categorical.

Usage

1
spatialSAOM(formula, data, subset, network, diffusion = list(), rateFix = 20, maxRounds = 10, method = "avSim", projname = "SAOM", ...)

Arguments

formula

an object of class "formula" (or one that can be coerced to that class): a symbolic description of the model to be fitted. Contains dependent variable and covariates, excluding the diffusion effect.

data

an optional data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model. If not found in data, the variables are taken from environment(formula), typically the environment from which spatialSAOM is called.

subset

an optional vector specifying a subset of observations to be used in the fitting process.

network

square connection matrix of all observations. The dimension must match the number of observations in the data frame.

diffusion

a list of covariates through which diffusion takes place, if not through the dependent variable.

rateFix

rate at which behavioral changes are fixed to guarantee estimation.

maxRounds

maximum number of iterations of the SAOM algorithm.

method

the method to be used; for fitting, currently only "avAlt" and "avSim" are supported.

projname

name under which temporary output is saved by the SAOM implementation.

...

not used.

Value

Returns an object of class sienaFit.

Author(s)

Johan A. Elkink and Thomas U. Grund

References


jelkink/spatialSAOM documentation built on Nov. 23, 2019, 12:05 a.m.