代码搜索：multivariate
找到约 564 项符合「multivariate」的源代码
代码结果 564
www.eeworm.com/read/483253/6601718
m gausprod.m
function [g,u,k]=gausprod(m,c)
%GAUSPROD calculates a product of gaussians [G,U,K]=(M,C)
% calculates the product of n d-dimensional multivariate gaussians
% this product is itself a gaussian
% In
www.eeworm.com/read/154843/11923367
m gausprod.m
function [g,u,k]=gausprod(m,c)
%GAUSPROD calculates a product of gaussians [G,U,K]=(M,C)
% calculates the product of n d-dimensional multivariate gaussians
% this product is itself a gaussian
% In
www.eeworm.com/read/342008/12046828
m gauss.m
%GAUSS Generation of multivariate Gaussian dataset.
%
% A = gauss(n,U,G)
%
% Generation of n k-dimensional Gaussian distributed vectors with
% covariance matrices G (size k*k*c) and with means, la
www.eeworm.com/read/223158/14651452
m gausprod.m
function [g,u,k]=gausprod(m,c)
%GAUSPROD calculates a product of gaussians [G,U,K]=(M,C)
% calculates the product of n d-dimensional multivariate gaussians
% this product is itself a gaussian
% In
www.eeworm.com/read/330303/3425731
hpp wienerprocess.hpp
#ifndef INDII_ML_AUX_WIENERPROCESS_HPP
#define INDII_ML_AUX_WIENERPROCESS_HPP
#include "StochasticProcess.hpp"
namespace indii {
namespace ml {
namespace aux {
/**
* Multivariate Wiener proc
www.eeworm.com/read/407072/2271015
hpp wienerprocess.hpp
#ifndef INDII_ML_AUX_WIENERPROCESS_HPP
#define INDII_ML_AUX_WIENERPROCESS_HPP
#include "StochasticProcess.hpp"
namespace indii {
namespace ml {
namespace aux {
/**
* Multivariate Wiener proc
www.eeworm.com/read/293183/8310198
m gauss.m
%GAUSS Generation of multivariate Gaussian dataset.
%
% A = gauss(n,U,G)
%
% Generation of n k-dimensional Gaussian distributed vectors with
% covariance matrices G (size k*k*c) and with means, la
www.eeworm.com/read/265721/11255560
m gausprod.m
function [g,u,k]=gausprod(m,c)
%GAUSPROD calculates a product of gaussians [G,U,K]=(M,C)
% calculates the product of n d-dimensional multivariate gaussians
% this product is itself a gaussian
% In
www.eeworm.com/read/389962/8490880
m snn.m
% SNN - Creates forecasts of a time series on t+1 using multivariate nearest neighbor algorithm.
%
% REQUIRES MREGRESS.M FILE available at http://www.mathworks.com/matlabcentral/fileexchange/l
www.eeworm.com/read/428849/8834402
pl references.pl
{
"Anderson62" =>"T.W.Anderson and R.R.Bahadur. Classification into two
multivariate normal distributions with differrentia covariance matrices.
Anals of Mathematical Statistics, 33:420--431, Ju