Task: Cholesky decomposition
C++: #include <cassert>
#include <cmath>
#include <iomanip>
#include <iostream>
#include <vector>

template <typename scalar_type> class matrix {
public:
    matrix(size_t rows, size_t columns)
        : rows_(rows), columns_(columns), elements_(rows * columns) {}

    matrix(size_t rows, size_t columns, scalar_type value)
        : rows_(rows), columns_(columns), elements_(rows * columns, value) {}

    matrix(size_t rows, size_t columns,
        const std::initializer_list<std::initializer_list<scalar_type>>& values)
        : rows_(rows), columns_(columns), elements_(rows * columns) {
        assert(values.size() <= rows_);
        size_t i = 0;
        for (const auto& row : values) {
            assert(row.size() <= columns_);
            std::copy(begin(row), end(row), &elements_[i]);
            i += columns_;
        }
    }

    size_t rows() const { return rows_; }
    size_t columns() const { return columns_; }

    const scalar_type& operator()(size_t row, size_t column) const {
        assert(row < rows_);
        assert(column < columns_);
        return elements_[row * columns_ + column];
    }
    scalar_type& operator()(size_t row, size_t column) {
        assert(row < rows_);
        assert(column < columns_);
        return elements_[row * columns_ + column];
    }
private:
    size_t rows_;
    size_t columns_;
    std::vector<scalar_type> elements_;
};

template <typename scalar_type>
void print(std::ostream& out, const matrix<scalar_type>& a) {
    size_t rows = a.rows(), columns = a.columns();
    out << std::fixed << std::setprecision(5);
    for (size_t row = 0; row < rows; ++row) {
        for (size_t column = 0; column < columns; ++column) {
            if (column > 0)
                out << ' ';
            out << std::setw(9) << a(row, column);
        }
        out << '\n';
    }
}

template <typename scalar_type>
matrix<scalar_type> cholesky_factor(const matrix<scalar_type>& input) {
    assert(input.rows() == input.columns());
    size_t n = input.rows();
    matrix<scalar_type> result(n, n);
    for (size_t i = 0; i < n; ++i) {
        for (size_t k = 0; k < i; ++k) {
            scalar_type value = input(i, k);
            for (size_t j = 0; j < k; ++j)
                value -= result(i, j) * result(k, j);
            result(i, k) = value/result(k, k);
        }
        scalar_type value = input(i, i);
        for (size_t j = 0; j < i; ++j)
            value -= result(i, j) * result(i, j);
        result(i, i) = std::sqrt(value);
    }
    return result;
}

void print_cholesky_factor(const matrix<double>& matrix) {
    std::cout << "Matrix:\n";
    print(std::cout, matrix);
    std::cout << "Cholesky factor:\n";
    print(std::cout, cholesky_factor(matrix));
}

int main() {
    matrix<double> matrix1(3, 3,
       {{25, 15, -5},
        {15, 18, 0},
        {-5, 0, 11}});
    print_cholesky_factor(matrix1);
    
    matrix<double> matrix2(4, 4,
       {{18, 22, 54, 42},
        {22, 70, 86, 62},
        {54, 86, 174, 134},
        {42, 62, 134, 106}});
    print_cholesky_factor(matrix2);

    return 0;
}

VB: Function Cholesky(Mat As Range) As Variant

Dim A() As Double, L() As Double, sum As Double, sum2 As Double
Dim m As Byte, i As Byte, j As Byte, k As Byte


    If Mat.Rows.Count <> Mat.Columns.Count Then
        MsgBox ("Correlation matrix is not square")
        Exit Function
    End If
    
    m = Mat.Rows.Count


    ReDim A(0 To m - 1, 0 To m - 1)
    ReDim L(0 To m - 1, 0 To m - 1)
    For i = 0 To m - 1
        For j = 0 To m - 1
            A(i, j) = Mat(i + 1, j + 1).Value2
            L(i, j) = 0
        Next j
    Next i


    Select Case m
        Case Is = 1
            L(0, 0) = Sqr(A(0, 0))
        
        Case Is = 2
            L(0, 0) = Sqr(A(0, 0))
            L(1, 0) = A(1, 0) / L(0, 0)
            L(1, 1) = Sqr(A(1, 1) - L(1, 0) * L(1, 0))
        
        Case Else
            L(0, 0) = Sqr(A(0, 0))
            L(1, 0) = A(1, 0) / L(0, 0)
            L(1, 1) = Sqr(A(1, 1) - L(1, 0) * L(1, 0))
            For i = 2 To m - 1
                sum2 = 0
                For k = 0 To i - 1
                    sum = 0
                    For j = 0 To k
                        sum = sum + L(i, j) * L(k, j)
                    Next j
                    L(i, k) = (A(i, k) - sum) / L(k, k)
                    sum2 = sum2 + L(i, k) * L(i, k)
                Next k
                L(i, i) = Sqr(A(i, i) - sum2)
            Next i
    End Select
    Cholesky = L
End Function