Hamiltonian Monte Carlo

randomnumbers.hpp
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1 //
2 // Created by Lars Gebraad on 7/10/17.
3 //
4 
13 #ifndef HMC_VSP_RANDOMNUMBERS_HPP
14 #define HMC_VSP_RANDOMNUMBERS_HPP
15 
16 #include <vector>
17 
18 const double PI = 3.14159265358979323846264338327;
25 double randn(double mean, double stdv);
33 std::vector<double> randn(std::vector<double> means, std::vector<double> stdv);
41 std::vector<double> randn(std::vector<double> stdv);
50 std::vector<double> randn_Cholesky(std::vector<double> mean, std::vector<std::vector<double>>
51 CholeskyLower_CovarianceMatrix);
60 std::vector<double> randn_Cholesky(std::vector<std::vector<double>> CholeskyLower_CovarianceMatrix);
66 std::vector<double> randn(std::vector<std::vector<double>> DiagonalCovarianceMatrix);
73 double randf(double min, double max);
74 
75 #endif //HMC_VSP_RANDOMNUMBERS_HPP
PI
const double PI
Definition: randomnumbers.hpp:18
randn
double randn(double mean, double stdv)
Draws from Gaussian (mean, standard deviation) using Box-Müller transform.
Definition: randomnumbers.cpp:17
randn_Cholesky
std::vector< double > randn_Cholesky(std::vector< double > mean, std::vector< std::vector< double >> CholeskyLower_CovarianceMatrix)
Drawing non-zero mean samples from an dimensional correlated Gaussian. Invokes randn_Cholesky(std::v...
Definition: randomnumbers.cpp:47
randf
double randf(double min, double max)
Draw uniformly distributed samples between two numbers.
Definition: randomnumbers.cpp:13
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