geo_fkf: Kriging method for Spatial Functional Data.

In geoFKF: Kriging Method for Spatial Functional Data

Kriging method for Spatial Functional Data.

Description

geo_fkf implements the kriging method for spatial functional datasets.

Usage

geo_fkf(m_data, m_coord, new_loc, p, t = seq(from = -pi, to = pi, by = 0.01))

Arguments

m_data	a tibble where each column or variable is data from a station
m_coord	a tibble with two columns: latitude and longitude
new_loc	a tible with one observation, where the columns or variables are latitude and longitude
p	order in the Fourier Polynomial
t	a time series with values belonging to [-π, π] to evaluate the estimate curve

Value

a list with three entries: estimates, Theta and cov_params

estimates

the estimate curve

Theta

weights (matrices) of the linear combination

cov_params

estimate σ^2, φ and ρ

Examples

data("datasetCanada")

m_data <- as.matrix(datasetCanada$m_data)
m_coord <- as.matrix(datasetCanada$m_coord[, 1:2])
pos <- sample.int(nrow(m_coord), 1)
log_pos <- !(seq_len(nrow(m_coord)) %in% pos)
new_loc <- m_coord[pos, ]
m_coord <- m_coord[log_pos, ]
m_data <- m_data[, log_pos]

geo_fkf(m_data, m_coord, new_loc)

geoFKF documentation built on Aug. 13, 2022, 1:05 a.m.