# Initialization error in Ordered Probit Model

**URL:** <https://discourse.mc-stan.org/t/initialization-error-in-ordered-probit-model/11361>\
**Category:** Modeling\
**Created:** [October 11, 2019, 4:33pm UTC](https://discourse.mc-stan.org/t/initialization-error-in-ordered-probit-model/11361 "2019-10-11T16:33:26Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![Apurva](https://avatars.discourse-cdn.com/v4/letter/a/dec6dc/32.png) [@Apurva](https://discourse.mc-stan.org/u/Apurva)\
**Post date:** [October 11, 2019, 4:33pm UTC](https://discourse.mc-stan.org/t/initialization-error-in-ordered-probit-model/11361/1 "2019-10-11T16:33:26Z")

</div>

Please share your Stan program and accompanying data if possible.

* * *

When including Stan code in your post it really helps if you make it as readable as possible by using Stan code chunks (```stan) with clear spacing and indentation. For example, use

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

```

instead of

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

* * *

To include mathematical notation in your post put LaTeX syntax between two `$` symbols, e.g.,  
p(\theta | y) \propto p(\theta) p(y | \theta).

#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 \<- x_g + beta_alpha + 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.

---

<div class="post-metadata">

**Author:** ![mcol](https://yyz2.discourse-cdn.com/flex030/user_avatar/discourse.mc-stan.org/mcol/32/5598_2.png) [@mcol](https://discourse.mc-stan.org/u/mcol)\
**Post date:** [October 12, 2019, 11:42am UTC](https://discourse.mc-stan.org/t/initialization-error-in-ordered-probit-model/11361/2 "2019-10-12T11:42:19Z")

</div>

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

> [@Apurva](#):
>
> row\_vector[N] u;  
> u[n] = x[n]\*g + beta[n]\*alpha + A[n] + b[n];

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)`