代码搜索：Multivariate Analysis
找到约 10,000 项符合「Multivariate Analysis」的源代码
代码结果 10,000
www.eeworm.com/read/408170/2253428
java statusprinter.java
/*******************************************************************************
** BonnMotion - a mobility scenario generation and analysis tool **
** Copyright (C) 2002, 2003 Universit
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java sortableinteger.java
/*******************************************************************************
** BonnMotion - a mobility scenario generation and analysis tool **
** Copyright (C) 2002, 2003 Universit
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tex moveout.tex
\section{Moveout analysis}
% ------------------------------------------------------------
\inputdir{flat}
% ------------------------------------------------------------
\plot{hyper}{width=6.0in}
{An i
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input-finite-mrf
/*
* =====================================================================
* Analysis of Five Story Steel Moment Resistant Frame
*
* Written By: Mark Austin O
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txt readme.txt
**************************************************************************
* Matlab source codes for the kernel direct discriminant analysis (KDDA) *
* Author: Lu Juwei
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c durbin.c
/*****************************************************************************
*
* NAME
* durbin
*
* FUNCTION
*
* Durbin recursion to do autocorrelation analysis.
* Converts autocorr
www.eeworm.com/read/428167/8885966
m gaussian_prob.m
function p = gaussian_prob(x, m, C, use_log)
% GAUSSIAN_PROB Evaluate a multivariate Gaussian density.
% p = gaussian_prob(X, m, C)
% p(i) = N(X(:,i), m, C) where C = covariance matrix and each COL
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m gaussian_prob.m
function p = gaussian_prob(x, m, C, use_log)
% GAUSSIAN_PROB Evaluate a multivariate Gaussian density.
% p = gaussian_prob(X, m, C)
% p(i) = N(X(:,i), m, C) where C = covariance matrix and each COL
www.eeworm.com/read/373249/9467813
m gaussian_prob.m
function p = gaussian_prob(x, m, C, use_log)
% GAUSSIAN_PROB Evaluate a multivariate Gaussian density.
% p = gaussian_prob(X, m, C)
% p(i) = N(X(:,i), m, C) where C = covariance matrix and each COL
www.eeworm.com/read/349646/10808458
m gaussian_prob.m
function p = gaussian_prob(x, m, C, use_log)
% GAUSSIAN_PROB Evaluate a multivariate Gaussian density.
% p = gaussian_prob(X, m, C)
% p(i) = N(X(:,i), m, C) where C = covariance matrix and each COL