posterior_predict() fails with newdata for models estimated with family = mgcv::betar

[martinmodrak]

Summary:

Similar to #324, I can run posterior_predict and posterior_linpred for betareg models, but as soon as I specify newdata = XX I get an error.

Description:

Running posterior_linpred with newdata (even if the newdata argument is the same as the data used to estimate the model) results in the following error:

Error in (function (optimizer = "nloptwrap", restart_edge = TRUE, boundary.tol = 1e-05, : unused arguments (tolPwrss = 1e-07, compDev = TRUE, nAGQ0initStep = TRUE, checkControl = list("ignore", "ignore", "ignore", "stop", "ignore", "message+drop.cols", "warning", "stop", "ignore"), checkConv = list(list("ignore", 0.001, NULL), list("ignore", 1e-04), list("ignore", 1e-06)))

The workaround mentioned in #324 (adding class) does not help.

Reproducible Steps:

library(rstanarm)
test <- data.frame(y = c(0.1, 0.3), x = c(TRUE, FALSE))

SEED=101
res <- stan_glmer(y ~ (1|x), family=mgcv::betar(link="logit"), data=test, seed = SEED, iter = 200)

class(res) <- c(class(res), "betareg") #Workaround from issue 324
P <- posterior_linpred(res, newdata=test)

RStanARM Version:

2.19.2

R Version:

3.6.0

Operating System:

Windows 10

[martinmodrak]

A duplicate of #406.

[jwdorrough]

@martinmodrak, not sure if this helps solve the issue but posterior_predict and posterior_linpred do run if newdata are specified and the predictions ignore the group level terms i.e. re.form=~0 or NA

library(rstanarm)
test <- data.frame(y = c(0.1, 0.3), x = c(TRUE, FALSE),B1=c(1,2))

SEED=101
res <- stan_glmer(y ~ (1|x), family=mgcv::betar(link="logit"), data=test, seed = SEED, iter = 200)
res1 <- stan_glmer(y ~ B1+(1|x), family=mgcv::betar(link="logit"), data=test, seed = SEED, iter = 200)

P <- posterior_linpred(res, newdata=test)#throws an error
P1<-posterior_linpred(res1, newdata=test)#throws an error
P2<-posterior_linpred(res1, newdata=test, re.form=~0)#runs

[jgabry]

I think this is finally fixed now. Sorry it took so long to get to this! The fix is now on the master branch and will be included in the next release.

[GitCJW]

I am still getting errors when using the posterior_* functions for betar models.
rstanarm: 2.21.1
rstan: 2.26.3
Win10

set.seed(123)
data <- data.frame(y=rbeta(100,100,200),x=rnorm(100))
fit <- rstanarm::stan_glm("y~x",data=data,family=mgcv::betar(link="logit"), chain=1)

# works
rstanarm::posterior_epred(fit, draws=100)
rstanarm::posterior_epred(fit, newdata=data.frame(x=1))

# Error in exp(eta) : non-numeric argument to mathematical function
rstanarm::posterior_predict(fit, draws=100) 
rstanarm::posterior_predict(fit, newdata=data.frame(x=1)) 

class(fit) <- c(class(fit), "betareg")

# works
rstanarm::posterior_epred(fit, draws=100)
rstanarm::posterior_predict(fit, draws=100) 

# Error in terms.formula(formula, data = data) : argument is not a valid model 
rstanarm::posterior_epred(fit, newdata=data.frame(x=1))
rstanarm::posterior_predict(fit, newdata=data.frame(x=1))