代码搜索：evaluate
找到约 3,619 项符合「evaluate」的源代码
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www.eeworm.com/read/273525/4207526
ado ml_eds.ado
*! version 6.0.1 18may2004
program define ml_eds /* list of score variables to be created */
version 6
if inlist("ml_e1","$ML_eval","$ML_evalf") {
// evaluate scores at solution
if "$ML_
www.eeworm.com/read/396844/2407677
m log_student_pdf.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/295456/8161013
m eval_ar_perf.m
function [ypred, ll, mse] = eval_AR_perf(coef, C, y, model)
% Evaluate the performance of an AR model.
%
% Inputs
% coef(:,:,k,m) - coef. matrix to use for k steps back, model m
% C(:,:,m) - cov
www.eeworm.com/read/195048/8175788
m eval_ar_perf.m
function [ypred, ll, mse] = eval_AR_perf(coef, C, y, model)
% Evaluate the performance of an AR model.
%
% Inputs
% coef(:,:,k,m) - coef. matrix to use for k steps back, model m
% C(:,:,m) - cov
www.eeworm.com/read/193669/8207847
c calculator.c
/*
calculator.c by Dr. Gerhard Wanderer (gerhard.wanderer@i-dail.de)
$Id: calculator.c,v 1.3 2002/12/17 15:31:55 gerhard Exp gerhard $
Subroutines to evaluate a string and calculate t
www.eeworm.com/read/392854/8322607
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/370521/9597816
m eval_ar_perf.m
function [ypred, ll, mse] = eval_AR_perf(coef, C, y, model)
% Evaluate the performance of an AR model.
%
% Inputs
% coef(:,:,k,m) - coef. matrix to use for k steps back, model m
% C(:,:,m) - cov
www.eeworm.com/read/411667/11234387
m eval_ar_perf.m
function [ypred, ll, mse] = eval_AR_perf(coef, C, y, model)
% Evaluate the performance of an AR model.
%
% Inputs
% coef(:,:,k,m) - coef. matrix to use for k steps back, model m
% C(:,:,m) - cov
www.eeworm.com/read/147186/12578660
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/147186/12579251
m eval_ar_perf.m
function [ypred, ll, mse] = eval_AR_perf(coef, C, y, model)
% Evaluate the performance of an AR model.
%
% Inputs
% coef(:,:,k,m) - coef. matrix to use for k steps back, model m
% C(:,:,m) - cov