This function provide model based parameters estiamtion for a geostatical model when spatial data are avialable at a corarser scale than their natural resolution. It is mainly for simulation purposing and testing.
splm_sim_aggr(data, mc_points = 100, tau.sq = 0, ncovariates = 2, beta = c(3.5, -1.2), aggr.cell = 9, fix.nugget = F, fix.nug = 0.5, ini = c(0.5, 0.5), message = F)
| data | A numeric vector of spatial data. |
|---|---|
| mc_points | Number of Monte Carlo points to calculate the correlation matrix. |
| tau.sq | Numeric value for the nugger parameter \(\tau^2\). |
| ncovariates | Number of covariates to simulate. |
| beta | Values for the beta parameters. |
| aggr.cell | To how many cells the points should be aggregated. |
| fix.nugget | A logical value. Should the nugget be fixed? |
| fix.nug | If fix.nugget = TRUE then a numeric value should be provided. |
| ini | Initial parameters values for the optimisation algorithm. |
| message | If FALSE suppress all the messages from the fitting algorithm. |