This function estimates variables observed at a "source" region into a "target" region. "Source" and "target" regions represent two different ways to divide a city, for example. For more details, see https://lcgodoy.me/smile/articles/sai.html.
ai(source, target, vars)ai_var(source, target, vars, vars_var, sc_vars = FALSE, var_method = "CS")
the target (of type sf) with estimates of the variables
observed at the source data.
a sf object - source spatial data.
a sf object - target spatial data.
a character representing the variables (observed at the
source) to be estimated at the target data.
a scalar of type character representing the name of
the variable in the source dataset that stores the variances of the
variable to be estimated at the target data.
boolean indicating whether vars should be scaled by its
observed variance (if available).
a character representing the method to approximate
the variance of the AI estimates. Possible values are "CS"
(Cauchy-Schwartz) or "MI" (Moran's I).