mSynch | R Documentation |
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.
mSynch(x, y = NULL, resamp = 999, na.rm = FALSE, circ = FALSE, quiet = FALSE)
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. |
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
).
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. |
Ottar N. Bjornstad onb1@psu.edu
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>
print.mSynch
# 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)
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