expand {deform} | R Documentation |
Fitting low-rank nonstationary spatial Gaussian process models through dimension expansion
Description
Function exapnd
fits a multi-dimensional dimension expansion model, where typically
x and y coordinates in geographic (G-) space will be provided and then scaled and
combined with new latent dimensions (that a functions of x and y) to give new coordinates
in deformed (D-) space in which isotropy of a Gaussian process is optimally achieved.
Usage
expand(
x,
z,
n,
k = 10,
lambda = rep(-1, length(k)),
lambda0 = rep(exp(3), length(k)),
correlation = FALSE,
cosine = FALSE,
trace = 0,
z0 = NULL,
standardise = "together"
)
Arguments
x |
a 2-column matrix comprising x and y coordinates column-wise, respectively, or a list; see Details for the latter |
z |
a variance-covariance matrix |
n |
an integer number of data |
k |
an integer vector of ranks |
lambda |
specified lambda values |
lambda0 |
initial lambda values |
correlation |
a logical defining whether |
cosine |
a logical defining whether the powered exponential covariance function should be multiplied by the cosine of scaled distances, i.e. giving a damped oscillation; defaults to |
trace |
an integer specifying the amount to report on optimisation (0, default, is nothing; 1 gives a bit) |
z0 |
a scalar giving initial values (which alternate |
standardise |
a character string that governs whether dimensions are scaled by a common ( |
Details
If x
is a list, then it wants elements "x"
, "z"
and "n"
as described above.
Value
An object of class deform
and then of class expansion
References
Bornn, L., Shaddick, G., & Zidek, J. V. (2012). Modeling nonstationary processes through dimension expansion. Journal of the American Statistical Association, 107(497), 281-289. doi:10.1080/01621459.2011.646919.
Examples
# one-dimensional expansion
data(solar)
expand(solar$x, solar$z, solar$n)
# equivalent to expand(solar)
# two-dimensional expansion with rank-8 and rank-5 dimensions
expand(solar$x, solar$z, solar$n, c(8, 5))