summary | R Documentation |
Generate summary statistics for posterior parameter estimates from a spatial fusion model.
## S3 method for class 'fusionModel'
summary(object, digits = 3, ...)
object |
object of class |
digits |
integer. The number of significant digits. |
... |
additional arguments not used. |
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.
Craig Wang
## example based on simulated data
if (requireNamespace("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 <- cbind(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),
inla.args = list(num.threads = "2:1"))
summary(mod_inla)
}
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