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/348694/10874338
m jackest.m
function[est,estall]=jackest(x,estfun,h,varargin)
% [est,estall]=jackest(x,estfun,h,PAR1,...)
%
% Parameter estimation based on the "Jackknife" procedure
%
% Inputs:
%
www.eeworm.com/read/466230/7041255
m ms_ar_fit.m
% Function for estimation of a Autoregressive Markov Switching model with k
% states and p lags (MS(k)-AR(p))
%
% The models swicthes in the whole mean equation including AR coefficients and cons
www.eeworm.com/read/299984/7140528
m testp.m
%TESTP Error estimation of Parzen classifier
%
% E = TESTP(A,H,T)
% E = TESTP(A,H)
%
% INPUT
% A input dataset
% H matrix smoothing parameters (optional, def: determined via
%
www.eeworm.com/read/462830/7195071
m statusbar.m
%Display a status/progress bar and inform about the elapsed
%as well as the remaining time (linear estimation).
%
%Synopsis:
%
% f=statusbar
% Get all status/progress bar handles.
%
% f=
www.eeworm.com/read/460435/7251003
m testp.m
%TESTP Error estimation of Parzen classifier
%
% E = TESTP(A,H,T)
% E = TESTP(A,H)
%
% INPUT
% A input dataset
% H matrix smoothing parameters (optional, def: determined via
%
www.eeworm.com/read/450939/7474355
m fastrobustsr.m
% Implements the fast and robust super-resolution method. This funtion
% first compute an estimation of the blurred HR image, using the median and
% shift method. It then uses the bilateral filter a
www.eeworm.com/read/450608/7480425
m testp.m
%TESTP Error estimation of Parzen classifier
%
% E = TESTP(A,H,T)
% E = TESTP(A,H)
%
% INPUT
% A input dataset
% H matrix smoothing parameters (optional, def: determined via
%
www.eeworm.com/read/450295/7486047
m ms_ar_fit.m
% Function for estimation of a Autoregressive Markov Switching model with k
% states and p lags (MS(k)-AR(p))
%
% The models swicthes in the whole mean equation including AR coefficients and cons
www.eeworm.com/read/449504/7502671
m dcc_mvgarch_likelihood.m
function [logL, Rt, likelihoods, Qt]=dcc_mvgarch_likelihood(params, stdresid, P, Q)
% PURPOSE:
% Restricted likelihood for use in the DCC_MVGARCH estimation and
% returns the likeliho
www.eeworm.com/read/449504/7502673
m idcc_mvgarch_full_likelihood.m
function [logL, Rt, likelihoods]=Idcc_garch_full_likelihood(parameters, data, archP,garchQ)
% PURPOSE:
% Full likelihood for use in the DCC_MVGARCH estimation and
% returns the likeli