Nothing
library(bsem)
library(magrittr)
library(testthat)
## Models (sem, print.bsem, summary.bsem, plot.bsem)
dt <- simdata(Nna = 1)
## factorial
fit <- bsem::sem(
data = dt$data %>% na.omit(),
blocks = dt$blocks,
signals = dt$signals,
iter = 2,
warmup = 0,
chains = 1
) %>%
expect_s3_class(class = "bsem")
fit$model == "factorial"
print.bsem(fit)
fit %>% summary()
fit %>% plot()
fit$mean_alpha %>% arrayplot()
### factorialNA
fit <- sem(
data = dt$data,
blocks = dt$blocks,
signals = dt$signals,
iter = 2,
warmup = 0,
chains = 1
) %>%
expect_s3_class(class = "bsem")
fit$model == "factorialNA"
print.bsem(fit)
fit %>% summary()
fit %>% plot()
fit$mean_alpha %>% arrayplot()
## factorialEX
fit <- sem(
data = dt$data %>% na.omit(),
blocks = dt$blocks,
exogenous = dt$exogenous,
signals = dt$signals,
iter = 2,
warmup = 0,
chains = 1
) %>%
expect_s3_class(class = "bsem")
fit$model == "factorialEX"
print.bsem(fit)
fit %>% summary()
fit %>% plot()
fit$mean_alpha %>% arrayplot()
### factorialNAEX
fit <- sem(
data = dt$data,
blocks = dt$blocks,
exogenous = dt$exogenous,
signals = dt$signals,
iter = 2,
warmup = 0,
chains = 1
) %>%
expect_s3_class(class = "bsem")
fit$model == "factorialNAEX"
print.bsem(fit)
fit %>% summary()
fit %>% plot()
fit$mean_alpha %>% arrayplot()
## sem
fit <- sem(
data = dt$data %>% na.omit(),
blocks = dt$blocks,
paths = dt$paths,
signals = dt$signals,
iter = 2,
warmup = 0,
chains = 1
) %>%
expect_s3_class(class = "bsem")
fit$model == "sem"
print.bsem(fit)
fit %>% summary()
fit %>% plot()
fit$mean_alpha %>% arrayplot()
### semNA
fit <- sem(
data = dt$data,
blocks = dt$blocks,
paths = dt$paths,
signals = dt$signals,
iter = 2,
warmup = 0,
chains = 1
) %>%
expect_s3_class(class = "bsem")
fit$model == "semNA"
print.bsem(fit)
fit %>% summary()
fit %>% plot()
fit$mean_alpha %>% arrayplot()
## semEX
fit <- sem(
data = dt$data %>% na.omit(),
blocks = dt$blocks,
paths = dt$paths,
exogenous = dt$exogenous,
signals = dt$signals,
iter = 2,
warmup = 0,
chains = 1
) %>%
expect_s3_class(class = "bsem")
fit$model == "semEX"
print.bsem(fit)
fit %>% summary()
fit %>% plot()
fit$mean_alpha %>% arrayplot()
### semNAEX
fit <- sem(
data = dt$data,
blocks = dt$blocks,
paths = dt$paths,
exogenous = dt$exogenous,
signals = dt$signals,
iter = 2,
warmup = 0,
chains = 1
) %>%
expect_s3_class(class = "bsem")
fit$model == "semNAEX"
print.bsem(fit)
fit %>% summary()
fit %>% plot()
fit$mean_alpha %>% arrayplot()
### handlers.R
## Prior options
expect_warning(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(
beta = "cauchy(0,1)",
sigma2 = "lognormal(-1,2)",
gamma = "cauchy(0,1)",
tau2 = "lognormal(-1,2)",
gamma0 = "cauchy(0,1)"
)
)
) %>% expect_s3_class(class = "bsem")
expect_warning(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(
beta = "normal(-2,1)",
sigma2 = "gamma(.1,.1)",
gamma = "cauchy(0,1)",
tau2 = "inv_gamma(1.1,2.2)",
gamma0 = "cauchy(0,1)"
)
)
) %>% expect_s3_class(class = "bsem")
expect_warning(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(
beta = "normal(-2,1)",
sigma2 = "inv_gamma(1.1,2.1)",
gamma = "cauchy(0,1)",
tau2 = "gamma(1.1,2.2)",
gamma0 = "cauchy(0,1)"
)
)
) %>% expect_s3_class(class = "bsem")
## Prior misspecification
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(beta = "gamma(0,1)")
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(gamma = "gamma(0,1)")
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(gamma0 = "gamma(0,1)")
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(sigma2 = "normal(.1,.1)")
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(tau2 = "normal(0,1)")
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(beta = "gamma")
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(taual = "gamma0(0,1)")
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(gamma = "gamma(0.1,.1)")
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(gamma = "lognormal(0,2)")
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(gammar = "normal(0,2)")
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(beta = "gammar(0,2)")
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(gamma = "gammar(0,2)")
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(gamma0 = "gammar(0,2)")
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(sigma2 = "nrlme(0,2)")
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(tau2 = "gammar(0,2)")
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(gamma = "normal(-1,-2)")
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(gamma0 = "normal(-1,-2)")
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(beta = "normal(-1,-2)")
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(tau2 = "inv_gamma(-1,1.2)")
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(tau2 = "inv_gamma(1,-1.2)")
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(sigma2 = "inv_gamma(-1,1.2)")
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
prior_specs = list(sigma2 = "inv_gamma(1,-1.2)")
)
)
## Stanformals
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
iter = 2,
warmup = 0,
chains = 1,
coress = 1
)
)
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
signals = dt$signals[-1],
iter = 2,
warmup = 0,
chains = 1
)
)
aux <- dt$signals
aux[[3]] <- 1
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
signals = aux,
iter = 2,
warmup = 0,
chains = 1
)
)
rm(aux)
aux <- dt$paths
names(aux)[2] <- "F6"
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
paths = aux,
signals = dt$signals,
iter = 2,
warmup = 0,
chains = 1
)
)
rm(aux)
aux <- dt$paths
aux[[1]][1] <- 3.5
expect_error(
sem(
data = dt$data,
blocks = dt$blocks,
paths = aux,
signals = dt$signals,
iter = 2,
warmup = 0,
chains = 1
)
)
rm(aux)
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