P-value is equal to NaN in covmtest

[bill.mouz]

I have a dataset that has daily data about Covid19 for many countries. I want to group them in such a way that the first country has the number one, the second country has the number two and so on. For this I have wrote the below code:

list_of_countries = unique(final_dataset$location) #the number of countries in the dataset is 145

final_dataset$group = NA

for(i in 1:length(list_of_countries)){

  country = list_of_countries[i]

  start = 1

  while (final_dataset$location[start]!= country) {

    start = start + 1
  }

  while (final_dataset$location[start] == country & start<=nrow(final_dataset)) {

    final_dataset$group[start] = i

    start = start + 1  
  }
}

I have done this successfully. Now, I want to check if the covariance matrices which correspond to the countries of the dataset are statistically equal.In other words, I want to check if the 145 covariance matrices are equal. I have found the covmtest() function in order to do this. So I wrote the below code:

covmtest(x = as.matrix(final_dataset[, 5:20]), ina = as.matrix(final_dataset[, 21]), a = 0.05)

and I got the below output:

M.test  p-value       df critical 
 NaN      NaN 19584.00 19910.66

I don't know why the p-value is NaN. I have searched a lot and I haven't found the solution yet. Does anyone know how to solve this error?