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/343227/11962618
m c_dgaus.m
function dens = c_dgaus(X, mu, Sigma)
%c_dgaus Computes a set of multivariate normal density values
% in the case of diagonal covariance matrices (MEX-file).
% Use : dens = c_dgaus(X, mu, Sigma)
www.eeworm.com/read/227522/14421553
m mvaar.m
function [x,e,Kalman,Q2] = mvaar(y,p,UC,mode,Kalman)
% Multivariate (Vector) adaptive AR estimation base on a multidimensional
% Kalman filer algorithm. A standard VAR model (A0=I) is implemented. The
www.eeworm.com/read/273525/4208410
hlp y_mvclusnh.hlp
{smcl}
{p 0 4}
{help contents:Top}
> {help y_stat:Statistics}
> {help y_mv:Multivariate analysis}
> {help y_mvclus:Cluster analysis}
{bind:> {bf:Nonhierarchical clustering}}
{p_end}
{hline}
www.eeworm.com/read/427909/8913063
m student_t_logprob.m
function L = log_student_pdf(X, mu, lambda, alpha)
% LOG_STUDENT_PDF Evaluate the log of the multivariate student-t distribution at a point
% L = log_student_pdf(X, mu, lambda, alpha)
%
% Each col
www.eeworm.com/read/373627/9446023
html mvrnorm.html
R: Simulate from a Multivariate Normal Distribution
www.eeworm.com/read/373249/9467872
m student_t_logprob.m
function L = log_student_pdf(X, mu, lambda, alpha)
% LOG_STUDENT_PDF Evaluate the log of the multivariate student-t distribution at a point
% L = log_student_pdf(X, mu, lambda, alpha)
%
% Each col
www.eeworm.com/read/164422/10108750
m student_t_logprob.m
function L = log_student_pdf(X, mu, lambda, alpha)
% LOG_STUDENT_PDF Evaluate the log of the multivariate student-t distribution at a point
% L = log_student_pdf(X, mu, lambda, alpha)
%
% Each column
www.eeworm.com/read/349646/10808496
m student_t_logprob.m
function L = log_student_pdf(X, mu, lambda, alpha)
% LOG_STUDENT_PDF Evaluate the log of the multivariate student-t distribution at a point
% L = log_student_pdf(X, mu, lambda, alpha)
%
% Each col
www.eeworm.com/read/349646/10809131
m student_t_logprob.m
function L = log_student_pdf(X, mu, lambda, alpha)
% LOG_STUDENT_PDF Evaluate the log of the multivariate student-t distribution at a point
% L = log_student_pdf(X, mu, lambda, alpha)
%
% Each col
www.eeworm.com/read/143425/6930480
m arfit.m
function [w, A, C, sbc, fpe, th]=arfit(v, pmin, pmax, selector, no_const)
%ARFIT Stepwise least squares estimation of multivariate AR model.
%
% [w,A,C,SBC,FPE,th]=ARFIT(v,pmin,pmax) produces estimat