demo/pval_2d_complex.r

In MixfMRI: Mixture fMRI Clustering Analysis

library(MixfMRI, quietly = TRUE)
set.seed(1234)

### Check 2d data.
da <- pval.2d.complex
id <- !is.na(da)
PV.gbd <- da[id]
hist(PV.gbd, nclass = 100, main = "p-value")

### Test 2d data.
id.loc <- which(id, arr.ind = TRUE)
X.gbd <- t(t(id.loc) / dim(da))
ret <- fclust(X.gbd, PV.gbd, K = 3)
print(ret)

### p-values of rest clusters.
ret.lrt <- lrt(PV.gbd, ret$class, K = 3)
print(ret.lrt)
ret.lrt2 <- lrt2(PV.gbd, ret$class, K = 3)
print(ret.lrt2)

### Plotting.
par(mfrow = c(2, 2), mar = c(0, 0, 2, 0))
plotpv(da, ret$posterior, ret$param,
       zlim = c(0.005, 0.008), main = "Mean of Beta Distribution")
plotpv(da, ret$posterior, ret$param,
       plot.mean = FALSE, main = "p-value")
par(mar = c(5.1, 4.1, 4.1, 2.1))
plotpvlegend(zlim = c(0.005, 0.008), main = "Mean of Beta Distribution")
plotpvlegend(zlim = c(0, 0.01), main = "p-value")