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    <p><strong>EDIT:</strong> I just realized you were, probably, talking about multivariate Gaussian distribution. In this case, I think, you'd need <em>N</em> normal distributions, each corresponding to an univariate distribution along one of the coordinates. Then, you generate <strong>random vector</strong>'s coordinates by sampling each of the distributions. Effectively, the edited code below represents <em>coordinates of 10 two-dimensional <strong>random vectors</strong></em>, using C++11 pseudo-random number generation (<a href="http://ideone.com/3OWsra" rel="nofollow">code on ideone.com</a>). Note, in the example given there will be correlation between the two coordinates, since there is correlation between consecutive pseudo-random numbers. One can try using two seeds with two generators with more sophisticated algorithms provided by the Standard library. However, I feel, there still might be a correlation, even using two different generators - one would have to investigate this issue to give a definite answer. </p> <pre><code>#include &lt;iostream&gt; #include &lt;vector&gt; #include &lt;random&gt; #include &lt;iomanip&gt; int main() { std::random_device device_random_; std::default_random_engine generator_(device_random_()); std::normal_distribution&lt;&gt; distribution_x_(1.0, 0.5); std::normal_distribution&lt;&gt; distribution_y_(10.0, 1.0); std::vector&lt;double&gt; vector_x_, vector_y_; for (int counter_(0); counter_ &lt; 10; ++counter_) { vector_x_.push_back(distribution_x_(generator_)); vector_y_.push_back(distribution_y_(generator_)); std::cout &lt;&lt; std::fixed &lt;&lt; std::setprecision(4) &lt;&lt; "(" &lt;&lt; vector_x_[counter_] &lt;&lt; ", " &lt;&lt; vector_y_[counter_] &lt;&lt; ")\n"; } return (0); } </code></pre> <p>Program output:</p> <pre><code>(0.2390, 10.3887) (1.1087, 9.5847) (1.0920, 9.3468) (1.1982, 11.6633) (0.8840, 11.0903) (0.5573, 8.5121) (0.6709, 11.4706) (1.1477, 9.4374) (0.8778, 11.0323) (0.8255, 9.7704) </code></pre>
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    1. POHow to create random Gaussian vector in c++?
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