context('species_mix generic functions negative binomial functions')
testthat::test_that('species_mix negative binomial', {
library(ecomix)
set.seed(42)
nsp <- 100
sam_form <- as.formula(paste0('cbind(',paste(paste0('spp',1:nsp),collapse = ','),")~x1+x2"))
alpha <- rnorm(nsp,-0.5, .5)
beta <- matrix(c(3.6,-3.6,
-2.5,-2.5,
1,-4.5),
3,2,byrow=TRUE)
# delta <- -.4
x <- runif(200,-2.5,2.5)
# u <- rnorm(400)
xpred <- seq(-2.5,2.5,length.out = 100)
upred <- matrix(seq(-2.5,2.5,length.out = 100),ncol=1)
matplot(xpred,(exp((cbind(xpred,xpred^2)%*%t(beta)))))
# matplot(xpred,(exp((cbind(xpred,xpred^2)%*%t(beta))-c(upred%*%delta))))
# matlines(xpred,)
dat <- data.frame(y=1, x1=x, x2=I(x)^2)#, u)
simulated_data <- species_mix.simulate(archetype_formula = sam_form,
species_formula = ~1,
all_formula = NULL,
dat = dat,
nArchetypes = 3,
alpha=alpha,
beta=beta,
# delta = delta,
family = "negative.binomial")
y <- as.matrix(simulated_data[,grep("spp",colnames(simulated_data))])
colSums(y>0)
X <- simulated_data[,-grep("spp",colnames(simulated_data))]
U <- NULL
# U <- X[,4,drop=FALSE]
# X <- X[,-4, drop=FALSE]
W <- as.matrix(X[,1,drop=FALSE])
X <- as.matrix(X[,-1])
offset <- rep(0,nrow(y))
weights <- rep(1,nrow(y))
spp_weights <- rep(1,ncol(y))
site_spp_weights <- matrix(1,nrow(y),ncol(y))
y_is_na <- matrix(FALSE,nrow(y),ncol(y))
G <- 3
S <- ncol(y)
control <- ecomix:::set_control_sam(list())
disty <- 4
size <- rep(1,nrow(y))
powers <- attr(simulated_data,"powers") # yeah baby
options(warn=1)
fm <- ecomix:::fit.ecm.sam(y, X, W, U, spp_weights, site_spp_weights, offset, y_is_na, G, S, disty, size, powers, control = ecomix:::set_control_sam(list(em_refit = 3,em_steps = 100)))
## now let's try and fit the optimisation
start_vals <- ecomix:::starting_values_wrapper(y, X, W, U, spp_weights, site_spp_weights, offset, y_is_na, G, S, disty, size, powers, control)
tmp <- ecomix:::sam_optimise(y, X, W, U, offset, spp_weights, site_spp_weights, y_is_na, S, G, disty, size, powers, start_vals = start_vals, control)
testthat::expect_length(tmp,21)
set.seed(123)
tmp <- ecomix:::species_mix.fit(y=y, X=X, W=W, U=U, G=G, S=S,
spp_weights=spp_weights,
site_spp_weights=site_spp_weights,
offset=offset, disty=disty, y_is_na=y_is_na, size=size, powers=powers,
control=ecomix:::set_control_sam(list(print_cpp_start_vals = TRUE)))
sp_form <- ~1
fm1 <- species_mix(archetype_formula = sam_form, species_formula = sp_form,
data = simulated_data, family = 'negative.binomial',
nArchetypes = 3)
testthat::expect_s3_class(fm1,'species_mix')
fm2 <- species_mix(sam_form, sp_form, data = simulated_data, family = 'negative.binomial',
nArchetypes = 3,control=list(ecm_prefit = FALSE))
testthat::expect_s3_class(fm2,'species_mix')
})
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