spatialfusion (version 0.6-6)

summary: Obtain summary of parameter estimates for a spatial fusion model

Description

Generate summary statistics for posterior parameter estimates from a spatial fusion model.

Usage

# S3 method for fusionModel
summary(object, digits = 3, ...)

Value

The returned value is a matrix containing the parameter estimates and their summary statistics. The names of fixed effect coefficients are covariate names followed by internal parameter names in parentheses. 'beta_p' denotes the coefficients for point data and 'beta_a' denotes the coefficients for lattice data.

Arguments

object

object of class fusionModel. Output of fusion().

digits

integer. The number of significant digits.

...

additional arguments not used.

Author

Craig Wang

Examples

## example based on simulated data
if (FALSE) {
if (require("INLA", quietly = TRUE)) {
dat <- fusionSimulate(n.point = 20, n.area = 10, n.grid = 2,
       psill = 1, phi = 1, nugget = 0, tau.sq = 0.5,
       point.beta = list(rbind(1,5)),
       area.beta = list(rbind(-1, 0.5)),
       distributions = c("normal","poisson"),
       design.mat = matrix(c(1,1,1)))

geo_data <- data.frame(x = dat$mrf[dat$sample.ind, "x"],
               y = dat$mrf[dat$sample.ind, "y"],
               cov.point = dat$data$X_point[,2],
               outcome = dat$data$Y_point[[1]])
lattice_data <- sp::SpatialPolygonsDataFrame(dat$poly,
                    data.frame(outcome = dat$data$Y_area[[1]],
                    cov.area = dat$data$X_area[,2]))

dat_inla <- fusionData(geo.data = geo_data, geo.formula = outcome ~ cov.point,
                lattice.data = lattice_data, lattice.formula = outcome ~ cov.area,
                pp.data = dat$data$lgcp.coords[[1]],
                distributions = c("normal","poisson"), method = "INLA")

mod_inla <- fusion(data = dat_inla, n.latent = 1, bans = 0,
                prior.range = c(1, 0.5), prior.sigma = c(1, 0.5),
                mesh.locs = dat_inla$locs_point, mesh.max.edge = c(0.5, 1))

summary(mod_inla)
}
}