C++: push_back() function doesn't append double values: segmentation core dumped

Question

I am having trouble with the push_back() function in C++. For a reason which I don't understand, the push_back function will "not accept" the value I am telling it to append, but the code works perfectly until I try to display the values I want (end of code). I have checked the value type, which is double, but it still won't append it.

The value I am trying to insert comes from a function which calculates the mean of a vector, taking out the NaN values. The code works perfectly but when I am trying to display the values I want, I always get: Segmentation fault (core dumped). This mean function first iterates over a range and creates a vector in which the NaN will be taken away. Then the mean will be calculated. I have spent quite some time on trying to figure out where the error could come from but wasn't able to figure out anything so any help would be highly appreciated. The following mean function:

double mean_func(double **arr, int iterations, int header, int start){

    std::vector<double> vec;
    for (int i=start-iterations; i < start; i++){
         vec.push_back(arr[i][header]);
         }

    vec.erase(std::remove_if(std::begin(vec),
                           std::end(vec),
                           [](const auto& value) { return std::isnan(value); }),
            std::end(vec));

    double sum = std::accumulate(vec.begin(), vec.end(), 0.0);
    double mean = sum / vec.size();

    return mean;
}

The whole code where transf_array_2_vec transforms a vector to an array.

#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <omp.h>
#include <cmath>
#include <vector>
#include <algorithm>
#include <iostream>
#include <numeric>
#include <typeinfo>


double** transf_vec_2_array(std::vector<std::vector<double> > vals, int N, int M)
{
   double** temp;
   temp = new double*[N];
   #pragma omp parallel for
   for(int i=0; (i < N); i++)
   {
      temp[i] = new double[M];
      for(int j=0; j < M; j++)
      {
          temp[i][j] = vals[i][j];
      }
   }
   return temp;
 }


double mean_func(double **arr, int iterations, int header, int start){

    std::vector<double> vec;
    for (int i=start-iterations; i < start; i++){
         vec.push_back(arr[i][header]);
         }

    vec.erase(std::remove_if(std::begin(vec),
                           std::end(vec),
                           [](const auto& value) { return std::isnan(value); }),
            std::end(vec));

    double sum = std::accumulate(vec.begin(), vec.end(), 0.0);
    double mean = sum / vec.size();

    return mean;
}


double** cfun(double **indata, unsigned int rows, unsigned int cols, int max_inputs, int daily_inputs, int weekly_inputs, int inputs_short_term, const char **header_1, const char **header_2, unsigned int size_header_1, unsigned int size_header_2, double **outdata) {

    std::vector< std::vector <double>> seq_collec;
    std::vector<double>seq;
    unsigned int i, j, k, l;
    unsigned int temp= 5080;

    int num = omp_get_thread_num();
    omp_set_num_threads(num);

    //#pragma omp parallel for //private(seq)
    for(i = max_inputs + weekly_inputs; i < temp ; i++) {
        for(j = 0; j < size_header_1; j++ ){
            for(k = 0; k < size_header_2 ; k++){
                for(l = i-max_inputs; l < i; l++){
                   if((strcmp(header_2[k],"price")==0)|| (strcmp(header_2[k], "change")==0)){
                    seq.push_back(indata[l][j+k]);
                      seq.push_back(mean_func(indata, inputs_short_term, j*size_header_2, l));
                      //std::cout << i << " " << j << " " << k <<std::endl;
                      //std::cout << header_1[j] << " " << header_2[k] << std::endl;
                      //std::cout << typeid(mean).name() << std::endl;
                      //std::cout << mean_func(indata, inputs_short_term, j*size_header_2, l) << std::endl;
                   }else{
                      seq.push_back(indata[l][j+k]);
                    //std::cout << header_1[k] << " " << header_2[k] << std::endl;
                  }
                }
            }
        seq.push_back(mean_func(indata, daily_inputs, j+k, l));
        seq.push_back(mean_func(indata, weekly_inputs, j+k, l));
       }
       //std::cout << seq.size() << std::endl;
       seq_collec.push_back(seq);
       seq.clear();
    }

    outdata = transf_vec_2_array(seq_collec, seq_collec.size(), seq_collec[0].size());
    //std::cout << seq_collec.size() << std::endl;
    //std::cout << seq_collec[0].size() << std::endl;
    return outdata;
}

int main(){

    int rows = 10846, cols = 12, max_inputs = 20, daily_inputs = 1000, weekly_inputs=5000, inputs_short_term=4;
    unsigned int size_header_1 = 3, size_header_2 = 4;
    const char *header_1[size_header_1] = {"CH:SMI","DJIA","RUI"};
    const char *header_2[size_header_2] = {"change","delta_vol","price","volume"};

    double* *indata = new double*[rows];
    double* *outdata = new double*[rows];
    for (int i=0; i < rows; i++){
        indata[i] = new double[cols];
        outdata[i] = new double[cols];
    }

    for (int i=0; i < rows; i++){
        for (int j=0; j < cols; j++){
          indata[i][j]=i + j ;
        }
    }

    outdata = cfun(indata, rows, cols, max_inputs, daily_inputs, weekly_inputs, inputs_short_term, header_1, header_2, size_header_1, size_header_2, outdata);

    for(int j = 0; j < 1; j++){
      for(int i = 0; i < 366; i++){
        std::cout << outdata[i][j] << std::endl; // PROBLEM HERE !!!
      }
    }

    return 0;
}