mSynch {ncf} | R Documentation |
The mean (cross-)correlation (with bootstrapp CI) for a panel of spatiotemporal data
Description
mSynch
is the function to estimate the mean (cross-)correlation in a spatiotemporal dataset as discussed in Bjornstad et al. (1999). The function requires multiple observations at each location.
Usage
mSynch(x, y = NULL, resamp = 999, na.rm = FALSE, circ = FALSE, quiet = FALSE)
Arguments
x |
matrix of dimension n x p representing p observation at each location (i.e. each row is a time series). |
y |
optional matrix of dimension m x p representing p observation at each location (i.e. each row is a time series). If provided, the mean cross-correlation between the two panels is computed. |
resamp |
the number of resamples for the bootstrap or the null distribution. |
na.rm |
If TRUE, NA's will be dealt with through pairwise deletion of missing values for each pair of time series – it will dump if any one pair has less than two (temporally) overlapping observations. |
circ |
If TRUE, the observations are assumed to be angular (in radians), and circular correlation is used. |
quiet |
If TRUE, the counter is suppressed during execution. |
Details
Missing values are allowed – values are assumed missing at random.
The circ argument computes a circular version of the Pearson's product moment correlation (see cor2
).
Value
An object of class "mSynch" is returned, consisting of a list with two components:
real |
the regional average correlation. |
boot |
a vector of bootstrap resamples. |
Author(s)
Ottar N. Bjornstad onb1@psu.edu
References
Bjornstad, O.N., Ims, R.A. & Lambin, X. (1999) Spatial population dynamics: Analysing patterns and processes of population synchrony. Trends in Ecology and Evolution, 11, 427-431. <doi:10.1016/S0169-5347(99)01677-8>
See Also
Examples
# first generate some sample data
x <- expand.grid(1:20, 1:5)[, 1]
y <- expand.grid(1:20, 1:5)[, 2]
# z data from an exponential random field
z <- cbind(
rmvn.spa(x = x, y = y, p = 2, method = "exp"),
rmvn.spa(x = x, y = y, p = 2, method = "exp")
)
# mean correlation analysis
fit1 <- mSynch(x = z, resamp = 500)
print(fit1)