Initialization error in Ordered Probit Model

Modeling
1

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model {
  vector[N] mu = alpha + beta * x;
  y ~ normal(mu, sigma); 
}

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model{
vector[N] mu = alpha+beta*x;
y~normal(mu,sigma);
}

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#preparing the data
library(rstan)
Sys.setenv(LOCAL_CPPFLAGS = ‘-march=native’)
rm(list=ls())
set.seed(1234)
x <- as.matrix(runif(n=10000, 1, 10))
beta <- rnorm(n=10000, 5, 2)
g <- 5
alpha <- 4
A <- rnorm(n=10000, 8, 4)#random effect
b <- rnorm(n=10000, 10, 3)#random effect
u <- xg + betaalpha + A + b
theta <- c(53,65,77)
z <- numeric(10000)

for (i in 1:10000) {
if (u[i] < 53) {
z[i] <- 1
} else if(53 <= u[i] & u[i] < 65){
z[i] <- 2
} else if(65 <= u[i] & u[i] < 77){
z[i] <- 3
} else {
z[i] <- 4
}
}

K=as.integer(4)
N = as.integer(10000)
D = as.integer(1)
sim_data <- list(K=as.integer(4),
N = as.integer(10000),
D = as.integer(1),
z = z,
x =x,
alpha = alpha,
beta = beta,
A = A,
b= b)

stanmodel_code <- ’
data {
int<lower=2> K;
int<lower=0> N;
int<lower=1> D;
int<lower=1,upper=K> z[N];
row_vector[D] x[N];
real alpha;
row_vector[N] beta;
row_vector[N] A;
row_vector[N] b;
}
parameters {
vector[D] g;
ordered[K-1] theta;
}
model {
vector[K] w;
for (n in 1:N) {
row_vector[N] u;
u[n] = x[n]*g + beta[n]*alpha + A[n] + b[n];
w[1] = 1 - Phi(u[1] - theta[1]);
for (k in 2:(K-1))
w[k] = Phi(u[n] - theta[k-1]) - Phi(u[n] - theta[k]);
w[K] = Phi(u[n] - theta[K-1]);
z[n] ~ categorical(w/sum(w));
}
}’

mod <- stan_model(model_code = stanmodel_code, verbose = TRUE)
fit <- sampling(mod, data = sim_data, iter= 1000)
fit_vb <- vb(mod)

list_of_draws_vb <- extract(fit_vb) #extract the output
mean(list_of_draws_vb$g)
mean(list_of_draws_vb$theta[,1])
mean(list_of_draws_vb$theta[,2])
mean(list_of_draws_vb$theta[,3])

This is the error:
Chain 1: Rejecting initial value:
Chain 1: Error evaluating the log probability at the initial value.
Chain 1: Exception: Phi: x is nan, but must not be nan! (in ‘model36a85db92aa4_99256f95fd8db93be7642f2f8c126869’ at line 22)

Chain 1:
Chain 1: Initialization between (-2, 2) failed after 100 attempts.
Chain 1: Try specifying initial values, reducing ranges of constrained values, or reparameterizing the model.
Error in sampler$call_sampler(c(args, dotlist)) : Initialization failed.

1 Like
2

I’ve tried to read through your code, and I think the problem is in this line:

Here you use g, which is defined before but never assigned any value. This may be the cause on the NaN error reported.

Note also that you define u as a row_vector, but you only ever reference one element at a time, so you could just declare a real.

On the R side, use 4L instead of as.integer(4)

2 Likes