hsarx | R Documentation |
Fit SAR, SARX, HSAR and HSARX models to data as described in Solymos and Lele (2012).
hsarx(formula, data, n.clones, cl = NULL, ...)
formula |
Formula. |
data |
Data. |
n.clones |
Number of clones to be used. |
cl |
Cluster object for parallel computations. |
... |
Other arguments for MCMC. |
Fit SAR, SARX, HSAR and HSARX models to data as described in Solymos and Lele (2012).
An S4 object object of class 'hsarx'. It inherits from 'dcMle', and has additional slots for storing the data.
Peter Solymos
Solymos, P. and Lele, S. R., 2012. Global pattern and local variation in species-area relationships. Global Ecology and Biogeography 21, 109–120.
sardata
for data sets.
## Not run:
## to reproduce results from Solymos and Lele (Table 1)
data(sardata)
DAT <- data.frame(sardata$islands,
sardata$studies[match(sardata$islands$study,
rownames(sardata$studies)),])
x <- hsarx(log(S+0.5) ~ log(A) | (taxon.group + island.type +
abs(latitude) + I(log(extent)))^2 | study, DAT,
n.clones=5, n.adapt=2000, n.update=3000, n.iter=1000)
## SAR
DATS <- DAT[1:191,]
(x1 <- hsarx(log(S+0.5) ~ log(A),
DATS[DATS$study=="abbott1978bird",], n.clones=2))
## SARX
DATS$rnd <- rnorm(nrow(DATS), log(DATS$extent))
(x2 <- hsarx(log(S+0.5) ~ log(A) * rnd,
DATS[DATS$study=="abbott1978bird",], n.clones=2))
## HSAR
(x3 <- hsarx(log(S+0.5) ~ log(A) | 1 | study,
DATS, n.clones=2, n.iter=1000))
## HSARX
(x4 <- hsarx(log(S+0.5) ~ log(A) | abs(latitude) | study,
DATS, n.clones=2, n.iter=1000))
## End(Not run)
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