title: c++ - implementing a multivariate probability density function for a likelihood filter
body: <p>I'm trying to construct a multivariate likelihood function in c++ code with the aim of comparing multiple temperature simulations for consistency with observations but taking into account autocorrelation between the time steps. I am inexperienced in c++ and so have been struggling to understand how to write the equation in c++ form. I have the covariance matrix, the simulations I wish to judge and the observations to compare to. The equation is as follows:</p>
  <p>f(x,μ,Σ) = (1/√(∣Σ∣(2π)^d))*exp(−1/2(x-μ)<em>Σ^(-1)</em>(x-μ)')</p>
  <p>So I need to find the determinant and the inverse of the covariance matrix. Does anyone know how to do that in c++ if x,μ and Σ are all specified?</p>