sarm: Estimate a Strategic Autoregressive Model

In milesdwilliams15/SARM: Tools for Estimating a Strategic Autoregressive Model

Description

This function takes a user supplied equation object and dataframe. It assumes that the first two variables on the right-hand side of the equation are the actor-specific resource constraint and the spatial lag (sum of other-actor expenditures on the strategic good), respectively. The remaining variables are assumed to predict intrinsic preference for the strategic good. NA values are allowable. By default, it is assumed that estimated standard errors are not robust, nor are they clustered according to some grouping variable. If robust standard errors are desired, the user should set robust = TRUE. If robust-clustered standard errors are desired, the user should set both robust = TRUE and cluster = TRUE. If clustered standard errors are desired, it is assumed that the last variable included on the right-hand side of the equation is the grouping variable. The grouping variable may be numeric, a factor, or a character string.

Usage

sarm(eq, data = NULL, robust = F, cluster = F)

milesdwilliams15/SARM documentation built on Jan. 17, 2020, 12:22 a.m.