tests/testthat/test-fitgllvm.R
In JenniNiku/gllvm: Generalized Linear Latent Variable Models
context("test-fitgllvm")
test_that("basic data fitting works", {
data(microbialdata)
X <- microbialdata$Xenv[1:30,]
y <- microbialdata$Y[1:30, order(colMeans(microbialdata$Y > 0), decreasing = TRUE)[21:35]]
f0<-gllvm(y, family = poisson(), seed = 999)
f1<-gllvm(y, family = "negative.binomial", seed = 999)
f2<-gllvm(y, X, formula = ~pH + Phosp, family = "negative.binomial", seed = 999)
expect_true(round(mean(f0$params$beta0), digits = 1)-2<0.01)
expect_true(round(mean(f1$params$beta0), digits = 1)-2<0.01)
expect_true(round(mean(f2$params$Xcoef[,1]), digits = 1)-0.1<0.01)
})
test_that("fourth corner models works", {
data(microbialdata)
X <- microbialdata$Xenv[1:30,2:3]
y <- microbialdata$Y[1:30, order(colMeans(microbialdata$Y > 0), decreasing = TRUE)[21:35]]
TR <- matrix(rnorm(15)); colnames(TR) <- "t1"
ff0<-gllvm(y, X, TR=TR, family = "negative.binomial", seed = 999)
ff1<-gllvm(y, X, TR=TR, formula = ~pH + pH:t1, family = "negative.binomial", seed = 999)
expect_true(is.finite(ff0$logL))
expect_true(is.finite(ff1$logL))
})
test_that("row effects works", {
data(microbialdata)
y <- microbialdata$Y[1:30, order(colMeans(microbialdata$Y > 0), decreasing = TRUE)[21:35]]
fr0<-gllvm(y, family = "negative.binomial", seed = 999, row.eff = "fixed", num.lv = 1)
fr1<-gllvm(y, family = "negative.binomial", seed = 999, row.eff = "random", num.lv = 0)
result<-c(-0.34, 0.29)
names(result)<-c("AB3", "sigma")
expect_true(round(fr0$params$row.params[2], digits = 2)- result[1]<0.1)
expect_true(round(fr1$params$sigma, digits = 2)- result[2]<0.1)
})
test_that("binomial works", {
data(microbialdata)
y <- microbialdata$Y[, order(colMeans(microbialdata$Y > 0), decreasing = TRUE)[160:175]]
y01<-(y>0)*1
fb0<-gllvm(y01, family = binomial(link = "logit"), seed = 999, method = "LA", num.lv = 1)
fb2<-gllvm(y01, family = binomial(link = "probit"), seed = 999)
expect_true(is.finite(fb0$logL))
expect_true(is.finite(fb2$logL))
})
test_that("ZIP works", {
data(eSpider)
spider <- eSpider
spider$abund <- eSpider$abund[eSpider$nonNA,]
y <- spider$abund[order(rowSums(spider$abund>0), decreasing = TRUE)[1:20],1:8]
fz0<-gllvm(y, family = "ZIP", seed = 999, method = "LA", num.lv = 1)
expect_equal( length(fz0$params$beta0), 8 )
expect_true( is.finite(fz0$logL))
})
test_that("quadratic models work", {
data(eSpider)
spider <- eSpider
spider$abund <- spider$abund[spider$nonNA,]
spider$x <- spider$X[spider$nonNA,]
X <- scale(spider$x)
y <- spider$abund
fq0<-gllvm(y, num.lv = 2, family = "poisson", seed = 999)
fq1<-gllvm(y, X, num.lv = 2, family = "poisson", seed = 999)
fq2<-gllvm(y, X, num.lv = 2, family = "poisson", row.eff="random", seed = 999)
expect_true(is.finite(fq0$logL))
expect_true(is.finite(fq1$logL))
expect_true(is.finite(fq2$logL))
})
test_that("constrained ordination models work", {
data(eSpider)
spider <- eSpider
spider$abund <- spider$abund[spider$nonNA,]
spider$x <- spider$X[spider$nonNA,]
X <- scale(spider$x)
y <- spider$abund
fc0<-gllvm(y, X, num.RR = 2, family = "poisson", seed = 999)
fc1<-gllvm(y, X, num.RR = 2, family = "poisson", seed = 999, randomB="LV")
fc2<-gllvm(y, X, num.RR = 2, family = "poisson", seed = 999, randomB="LV", row.eff="random")
fc3<-gllvm(y, X, num.RR = 2, quadratic=T, family = "poisson", seed = 9226, randomB="LV", row.eff="random")
expect_true(is.finite(fc0$logL))
expect_true(is.finite(fc1$logL))
expect_true(is.finite(fc2$logL))
expect_true(is.finite(fc3$logL))
})
test_that("concurrent ordination models work", {
data(eSpider)
spider <- eSpider
spider$abund <- spider$abund[spider$nonNA,]
spider$x <- spider$X[spider$nonNA,]
X <- scale(spider$x)
y <- spider$abund
fc0<-gllvm(y, X, num.lv.c = 2, family = "poisson", seed = 999)
fc1<-gllvm(y, X, num.lv.c = 2, family = "poisson", seed = 999, randomB="LV")
#this has a warning for overfitting that can be ignored
suppressWarnings(fc2<-gllvm(y, X, num.lv.c = 2, family = "poisson", seed = 999, randomB="LV", row.eff="random"))
fc3<-gllvm(y, X, num.lv.c = 2, quadratic=T, family = "poisson", seed = 999, randomB="LV")
expect_true(is.finite(fc0$logL))
expect_true(is.finite(fc1$logL))
expect_true(is.finite(fc2$logL))
expect_true(is.finite(fc3$logL))
})
test_that("phylogenetic models work", {
data(eSpider)
spider <- eSpider
spider$abund <- spider$abund[spider$nonNA,]
spider$x <- spider$X[spider$nonNA,]
X <- scale(spider$x)
y <- spider$abund
colMat=matrix(rnorm(12*12),12,12)
colMat<-colMat%*%t(colMat)
dist=abs(colMat)
colnames(dist)<-colnames(colMat)<-1:12
expect_error({model<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),num.lv=0, sd.errors = FALSE)})
colnames(colMat)<-row.names(colMat)<-colnames(dist)<-row.names(dist)<-colnames(spider$abund)
expect_error({model<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=colMat,colMat.rho.struct="term",num.lv=0, sd.errors=FALSE)})
expect_warning({model<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=colMat,Ab.struct="diagonal", num.lv=0, sd.errors = FALSE)})
#trait models are not yet tested in the following, just basic infrastructure for phylogenetic rando effects
suppressMessages(invisible(capture.output({
model11<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="diagonal",Ab.struct.rank=12,beta0com=TRUE)
model12<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="blockdiagonal",Ab.struct.rank=12,beta0com=TRUE)
model13<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="MNdiagonal",Ab.struct.rank=12,beta0com=TRUE)
model14<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="MNunstructured",Ab.struct.rank=12,beta0com=TRUE)
model15<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="spblockdiagonal",Ab.struct.rank=12,beta0com=TRUE)
model16<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="diagonalCL1",Ab.struct.rank=12,beta0com=TRUE)
model17<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="CL1",Ab.struct.rank=12,beta0com=TRUE)
model18<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="CL2",Ab.struct.rank=12,beta0com=TRUE)
model19<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="unstructured",Ab.struct.rank=1e3,beta0com=TRUE)
model21<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="diagonal",Ab.struct.rank=12,beta0com=TRUE)
model22<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="blockdiagonal",Ab.struct.rank=12,beta0com=TRUE)
model23<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="MNdiagonal",Ab.struct.rank=12,beta0com=TRUE)
model24<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="MNunstructured",Ab.struct.rank=12,beta0com=TRUE)
model25<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="spblockdiagonal",Ab.struct.rank=12,beta0com=TRUE)
model26<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="diagonalCL1",Ab.struct.rank=12,beta0com=TRUE)
model27<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="CL1",Ab.struct.rank=12,beta0com=TRUE)
model28<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="CL2",Ab.struct.rank=12,beta0com=TRUE)
model29<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="unstructured",Ab.struct.rank=1e3,beta0com=TRUE)
model31<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="diagonal",Ab.struct.rank=1,beta0com=TRUE)
model32<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="blockdiagonal",Ab.struct.rank=1,beta0com=TRUE)
model33<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="MNdiagonal",Ab.struct.rank=1,beta0com=TRUE)
model34<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="MNunstructured",Ab.struct.rank=1,beta0com=TRUE)
model35<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="spblockdiagonal",Ab.struct.rank=1,beta0com=TRUE)
model36<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="diagonalCL1",Ab.struct.rank=1,beta0com=TRUE)
model37<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="CL1",Ab.struct.rank=1,beta0com=TRUE)
model38<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="CL2",Ab.struct.rank=1,beta0com=TRUE)
model39<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="unstructured",Ab.struct.rank=1,beta0com=TRUE)
model41<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="diagonal",Ab.struct.rank=1,beta0com=TRUE)
model42<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="blockdiagonal",Ab.struct.rank=1,beta0com=TRUE)
model43<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="MNdiagonal",Ab.struct.rank=1,beta0com=TRUE)
model44<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="MNunstructured",Ab.struct.rank=1,beta0com=TRUE)
model45<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="spblockdiagonal",Ab.struct.rank=1,beta0com=TRUE)
model46<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="diagonalCL1",Ab.struct.rank=1,beta0com=TRUE)
model47<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="CL1",Ab.struct.rank=1,beta0com=TRUE)
model48<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="CL2",Ab.struct.rank=1,beta0com=TRUE)
model49<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="unstructured",Ab.struct.rank=1,beta0com=TRUE)
})))
expect_true(is.finite(model11$logL))
expect_true(is.finite(model12$logL))
expect_true(is.finite(model13$logL))
expect_true(is.finite(model14$logL))
expect_true(is.finite(model15$logL))
expect_true(is.finite(model16$logL))
expect_true(is.finite(model17$logL))
expect_true(is.finite(model18$logL))
expect_true(is.finite(model19$logL))
expect_true(is.finite(model21$logL))
expect_true(is.finite(model22$logL))
expect_true(is.finite(model23$logL))
expect_true(is.finite(model24$logL))
expect_true(is.finite(model25$logL))
expect_true(is.finite(model26$logL))
expect_true(is.finite(model27$logL))
expect_true(is.finite(model28$logL))
expect_true(is.finite(model29$logL))
expect_true(is.finite(model31$logL))
expect_true(is.finite(model32$logL))
expect_true(is.finite(model33$logL))
expect_true(is.finite(model34$logL))
expect_true(is.finite(model35$logL))
expect_true(is.finite(model36$logL))
expect_true(is.finite(model37$logL))
expect_true(is.finite(model38$logL))
expect_true(is.finite(model39$logL))
expect_true(is.finite(model41$logL))
expect_true(is.finite(model42$logL))
expect_true(is.finite(model43$logL))
expect_true(is.finite(model44$logL))
expect_true(is.finite(model45$logL))
expect_true(is.finite(model46$logL))
expect_true(is.finite(model47$logL))
expect_true(is.finite(model48$logL))
expect_true(is.finite(model49$logL))
})
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context("test-fitgllvm")
test_that("basic data fitting works", {
data(microbialdata)
X <- microbialdata$Xenv[1:30,]
y <- microbialdata$Y[1:30, order(colMeans(microbialdata$Y > 0), decreasing = TRUE)[21:35]]
f0<-gllvm(y, family = poisson(), seed = 999)
f1<-gllvm(y, family = "negative.binomial", seed = 999)
f2<-gllvm(y, X, formula = ~pH + Phosp, family = "negative.binomial", seed = 999)
expect_true(round(mean(f0$params$beta0), digits = 1)-2<0.01)
expect_true(round(mean(f1$params$beta0), digits = 1)-2<0.01)
expect_true(round(mean(f2$params$Xcoef[,1]), digits = 1)-0.1<0.01)
})
test_that("fourth corner models works", {
data(microbialdata)
X <- microbialdata$Xenv[1:30,2:3]
y <- microbialdata$Y[1:30, order(colMeans(microbialdata$Y > 0), decreasing = TRUE)[21:35]]
TR <- matrix(rnorm(15)); colnames(TR) <- "t1"
ff0<-gllvm(y, X, TR=TR, family = "negative.binomial", seed = 999)
ff1<-gllvm(y, X, TR=TR, formula = ~pH + pH:t1, family = "negative.binomial", seed = 999)
expect_true(is.finite(ff0$logL))
expect_true(is.finite(ff1$logL))
})
test_that("row effects works", {
data(microbialdata)
y <- microbialdata$Y[1:30, order(colMeans(microbialdata$Y > 0), decreasing = TRUE)[21:35]]
fr0<-gllvm(y, family = "negative.binomial", seed = 999, row.eff = "fixed", num.lv = 1)
fr1<-gllvm(y, family = "negative.binomial", seed = 999, row.eff = "random", num.lv = 0)
result<-c(-0.34, 0.29)
names(result)<-c("AB3", "sigma")
expect_true(round(fr0$params$row.params[2], digits = 2)- result[1]<0.1)
expect_true(round(fr1$params$sigma, digits = 2)- result[2]<0.1)
})
test_that("binomial works", {
data(microbialdata)
y <- microbialdata$Y[, order(colMeans(microbialdata$Y > 0), decreasing = TRUE)[160:175]]
y01<-(y>0)*1
fb0<-gllvm(y01, family = binomial(link = "logit"), seed = 999, method = "LA", num.lv = 1)
fb2<-gllvm(y01, family = binomial(link = "probit"), seed = 999)
expect_true(is.finite(fb0$logL))
expect_true(is.finite(fb2$logL))
})
test_that("ZIP works", {
data(eSpider)
spider <- eSpider
spider$abund <- eSpider$abund[eSpider$nonNA,]
y <- spider$abund[order(rowSums(spider$abund>0), decreasing = TRUE)[1:20],1:8]
fz0<-gllvm(y, family = "ZIP", seed = 999, method = "LA", num.lv = 1)
expect_equal( length(fz0$params$beta0), 8 )
expect_true( is.finite(fz0$logL))
})
test_that("quadratic models work", {
data(eSpider)
spider <- eSpider
spider$abund <- spider$abund[spider$nonNA,]
spider$x <- spider$X[spider$nonNA,]
X <- scale(spider$x)
y <- spider$abund
fq0<-gllvm(y, num.lv = 2, family = "poisson", seed = 999)
fq1<-gllvm(y, X, num.lv = 2, family = "poisson", seed = 999)
fq2<-gllvm(y, X, num.lv = 2, family = "poisson", row.eff="random", seed = 999)
expect_true(is.finite(fq0$logL))
expect_true(is.finite(fq1$logL))
expect_true(is.finite(fq2$logL))
})
test_that("constrained ordination models work", {
data(eSpider)
spider <- eSpider
spider$abund <- spider$abund[spider$nonNA,]
spider$x <- spider$X[spider$nonNA,]
X <- scale(spider$x)
y <- spider$abund
fc0<-gllvm(y, X, num.RR = 2, family = "poisson", seed = 999)
fc1<-gllvm(y, X, num.RR = 2, family = "poisson", seed = 999, randomB="LV")
fc2<-gllvm(y, X, num.RR = 2, family = "poisson", seed = 999, randomB="LV", row.eff="random")
fc3<-gllvm(y, X, num.RR = 2, quadratic=T, family = "poisson", seed = 9226, randomB="LV", row.eff="random")
expect_true(is.finite(fc0$logL))
expect_true(is.finite(fc1$logL))
expect_true(is.finite(fc2$logL))
expect_true(is.finite(fc3$logL))
})
test_that("concurrent ordination models work", {
data(eSpider)
spider <- eSpider
spider$abund <- spider$abund[spider$nonNA,]
spider$x <- spider$X[spider$nonNA,]
X <- scale(spider$x)
y <- spider$abund
fc0<-gllvm(y, X, num.lv.c = 2, family = "poisson", seed = 999)
fc1<-gllvm(y, X, num.lv.c = 2, family = "poisson", seed = 999, randomB="LV")
#this has a warning for overfitting that can be ignored
suppressWarnings(fc2<-gllvm(y, X, num.lv.c = 2, family = "poisson", seed = 999, randomB="LV", row.eff="random"))
fc3<-gllvm(y, X, num.lv.c = 2, quadratic=T, family = "poisson", seed = 999, randomB="LV")
expect_true(is.finite(fc0$logL))
expect_true(is.finite(fc1$logL))
expect_true(is.finite(fc2$logL))
expect_true(is.finite(fc3$logL))
})
test_that("phylogenetic models work", {
data(eSpider)
spider <- eSpider
spider$abund <- spider$abund[spider$nonNA,]
spider$x <- spider$X[spider$nonNA,]
X <- scale(spider$x)
y <- spider$abund
colMat=matrix(rnorm(12*12),12,12)
colMat<-colMat%*%t(colMat)
dist=abs(colMat)
colnames(dist)<-colnames(colMat)<-1:12
expect_error({model<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),num.lv=0, sd.errors = FALSE)})
colnames(colMat)<-row.names(colMat)<-colnames(dist)<-row.names(dist)<-colnames(spider$abund)
expect_error({model<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=colMat,colMat.rho.struct="term",num.lv=0, sd.errors=FALSE)})
expect_warning({model<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=colMat,Ab.struct="diagonal", num.lv=0, sd.errors = FALSE)})
#trait models are not yet tested in the following, just basic infrastructure for phylogenetic rando effects
suppressMessages(invisible(capture.output({
model11<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="diagonal",Ab.struct.rank=12,beta0com=TRUE)
model12<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="blockdiagonal",Ab.struct.rank=12,beta0com=TRUE)
model13<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="MNdiagonal",Ab.struct.rank=12,beta0com=TRUE)
model14<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="MNunstructured",Ab.struct.rank=12,beta0com=TRUE)
model15<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="spblockdiagonal",Ab.struct.rank=12,beta0com=TRUE)
model16<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="diagonalCL1",Ab.struct.rank=12,beta0com=TRUE)
model17<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="CL1",Ab.struct.rank=12,beta0com=TRUE)
model18<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="CL2",Ab.struct.rank=12,beta0com=TRUE)
model19<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="unstructured",Ab.struct.rank=1e3,beta0com=TRUE)
model21<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="diagonal",Ab.struct.rank=12,beta0com=TRUE)
model22<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="blockdiagonal",Ab.struct.rank=12,beta0com=TRUE)
model23<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="MNdiagonal",Ab.struct.rank=12,beta0com=TRUE)
model24<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="MNunstructured",Ab.struct.rank=12,beta0com=TRUE)
model25<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="spblockdiagonal",Ab.struct.rank=12,beta0com=TRUE)
model26<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="diagonalCL1",Ab.struct.rank=12,beta0com=TRUE)
model27<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="CL1",Ab.struct.rank=12,beta0com=TRUE)
model28<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="CL2",Ab.struct.rank=12,beta0com=TRUE)
model29<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="unstructured",Ab.struct.rank=1e3,beta0com=TRUE)
model31<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="diagonal",Ab.struct.rank=1,beta0com=TRUE)
model32<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="blockdiagonal",Ab.struct.rank=1,beta0com=TRUE)
model33<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="MNdiagonal",Ab.struct.rank=1,beta0com=TRUE)
model34<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="MNunstructured",Ab.struct.rank=1,beta0com=TRUE)
model35<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="spblockdiagonal",Ab.struct.rank=1,beta0com=TRUE)
model36<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="diagonalCL1",Ab.struct.rank=1,beta0com=TRUE)
model37<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="CL1",Ab.struct.rank=1,beta0com=TRUE)
model38<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="CL2",Ab.struct.rank=1,beta0com=TRUE)
model39<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="single",Ab.struct="unstructured",Ab.struct.rank=1,beta0com=TRUE)
model41<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="diagonal",Ab.struct.rank=1,beta0com=TRUE)
model42<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="blockdiagonal",Ab.struct.rank=1,beta0com=TRUE)
model43<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="MNdiagonal",Ab.struct.rank=1,beta0com=TRUE)
model44<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="MNunstructured",Ab.struct.rank=1,beta0com=TRUE)
model45<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="spblockdiagonal",Ab.struct.rank=1,beta0com=TRUE)
model46<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="diagonalCL1",Ab.struct.rank=1,beta0com=TRUE)
model47<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="CL1",Ab.struct.rank=1,beta0com=TRUE)
model48<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="CL2",Ab.struct.rank=1,beta0com=TRUE)
model49<-gllvm(spider$abund,X=spider$x,formula=~nocorr(ConWate+CovMoss|1),family="poisson",colMat=list(colMat,dist=dist),nn.colMat=3,num.lv=0,colMat.rho.struct="term",Ab.struct="unstructured",Ab.struct.rank=1,beta0com=TRUE)
})))
expect_true(is.finite(model11$logL))
expect_true(is.finite(model12$logL))
expect_true(is.finite(model13$logL))
expect_true(is.finite(model14$logL))
expect_true(is.finite(model15$logL))
expect_true(is.finite(model16$logL))
expect_true(is.finite(model17$logL))
expect_true(is.finite(model18$logL))
expect_true(is.finite(model19$logL))
expect_true(is.finite(model21$logL))
expect_true(is.finite(model22$logL))
expect_true(is.finite(model23$logL))
expect_true(is.finite(model24$logL))
expect_true(is.finite(model25$logL))
expect_true(is.finite(model26$logL))
expect_true(is.finite(model27$logL))
expect_true(is.finite(model28$logL))
expect_true(is.finite(model29$logL))
expect_true(is.finite(model31$logL))
expect_true(is.finite(model32$logL))
expect_true(is.finite(model33$logL))
expect_true(is.finite(model34$logL))
expect_true(is.finite(model35$logL))
expect_true(is.finite(model36$logL))
expect_true(is.finite(model37$logL))
expect_true(is.finite(model38$logL))
expect_true(is.finite(model39$logL))
expect_true(is.finite(model41$logL))
expect_true(is.finite(model42$logL))
expect_true(is.finite(model43$logL))
expect_true(is.finite(model44$logL))
expect_true(is.finite(model45$logL))
expect_true(is.finite(model46$logL))
expect_true(is.finite(model47$logL))
expect_true(is.finite(model48$logL))
expect_true(is.finite(model49$logL))
})
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