代码搜索：ESTIMATION
找到约 3,786 项符合「ESTIMATION」的源代码
代码结果 3,786
www.eeworm.com/read/449504/7502983
m sem_gmmd4.m
% PURPOSE: A Monte Carlo example of using sem_gmm
% GM estimation of the spatial error model
% in a Monte Carlo experiment
%---------------------------------------------------
% USAGE: sem_gmmd4
www.eeworm.com/read/441410/7670768
m recclock.m
function offset = recclock(ofile, navfile)
% RECCLOCK Estimation of receiver clock offset and position
% through batch processing. Data are read from
% the RINEX ofile.
%
www.eeworm.com/read/441245/7673006
m parzenml.m
%PARZENML Optimum smoothing parameter in Parzen density estimation.
%
% H = PARZENML(A)
%
% INPUT
% A Input dataset
%
% OUTPUT
% H Scalar smoothing parameter (in case of crisp labels)
%
www.eeworm.com/read/440842/7680327
m olsrs.m
function results = olsrs(y,x,R,q)
% PURPOSE: Restricted least-squares estimation
% y = Xb + e with the constraint that q = Rb
%---------------------------------------------------
% USAGE: results
www.eeworm.com/read/198546/7929029
m fattailed_garchlikelihood.m
function [LLF, h, likelihoods] = fattailed_garchlikelihood(parameters , data , p , q, errortype, stdEstimate, T)
% PURPOSE:
% Likelihood for fattailed garch estimation
%
% USAGE:
% [LLF,
www.eeworm.com/read/397102/8068265
m meancov.m
%MEANCOV Means and covariance estimation from multiclass data
%
% [U,G] = meancov(A)
%
% Computation of a set of mean vectors U and a set of covariance
% matrices G of the classes in the dataset A
www.eeworm.com/read/291067/6302896
m plotenosrc.m
function plotenosrc(snr, noTrials, realNoSrc, noSrcEst, meanNoSrc, stdNoSrc, detProbEq, detProbGE, plotIx, legendStr,startFigNr)
%PLOTENOSRC Plotting results from estimation of the number of signal s
www.eeworm.com/read/492929/6414243
m olsrs.m
function results = olsrs(y,x,R,q)
% PURPOSE: Restricted least-squares estimation
% y = Xb + e with the constraint that q = Rb
%---------------------------------------------------
% USAGE: results
www.eeworm.com/read/485544/6552829
m contents.m
% ReBEL : Recursive Bayesian Estimation Library - Toolkit
% Version 0.2
%
% ---CORE ROUTINES---
%
% ReBEL Inference System Routines
% consistent - Check ReBEL data structures for consisten
www.eeworm.com/read/480200/6668127
m reducesolvem.m
%
% Internal routines for solving the quadratic minimization problem
% occurring for "reduced set density estimation" (RSDE)
% implemented by the function "@kde/reduce.m"
%
% Code by (a) Chao He a