/// <summary>
 /// Computes the Cholesky decomposition for a matrix.
 /// </summary>
 /// <param name="matrix">The matrix to factor.</param>
 /// <returns>The Cholesky decomposition object.</returns>
 public static Cholesky Cholesky(this Matrix <float> matrix)
 {
     return((Cholesky)Cholesky <float> .Create(matrix));
 }
Example #2
0
 /// <summary>
 /// Computes the Cholesky decomposition for a matrix.
 /// </summary>
 /// <param name="matrix">The matrix to factor.</param>
 /// <returns>The Cholesky decomposition object.</returns>
 public static Cholesky Cholesky(this Matrix <Complex32> matrix)
 {
     return((Cholesky)Cholesky <Complex32> .Create(matrix));
 }
Example #3
0
        /// <summary>
        /// Samples a vector normal distributed random variable.
        /// </summary>
        /// <param name="rnd">The random number generator to use.</param>
        /// <param name="mean">The mean of the vector normal distribution.</param>
        /// <param name="covariance">The covariance matrix of the vector normal distribution.</param>
        /// <returns>a sequence of samples from defined distribution.</returns>
        private static Vector <double> SampleVectorNormal(Random rnd, Vector <double> mean, Matrix <double> covariance)
        {
            var chol = Cholesky <double> .Create(covariance);

            return(SampleVectorNormal(rnd, mean, chol));
        }