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/198546/7928909
m garchpq.m
function [parameters, likelihood, ht, stderrors, robustSE, scores, grad] = garchpq(data , p , q , startingvals, options)
% PURPOSE:
% GARCH(P,Q) parameter estimation with normal innovations usin
www.eeworm.com/read/198546/7928913
m fattailed_garchlikelihood2.m
function [LLF, h, likelihoods] = fattailed_garchlikelihood(parameters , data , p , q, errortype, stdEstimate, stdEstimate2, T, breakpt)
% PURPOSE:
% Likelihood for fattailed garch estimation
%
www.eeworm.com/read/198546/7928948
m garchpq_eviews.m
function [parameters, likelihood, ht, stderrors, robustSE, scores, grad] = garchpq(data , p , q , startingvals, options)
% PURPOSE:
% GARCH(P,Q) parameter estimation with normal innovations usin
www.eeworm.com/read/198546/7929070
m maxcore.m
function [e,E]=maxcore(regressand,parameters,ma,tau);
% PURPOSE:
% Forward recursion for armax estimation
%
% USAGE:
% [e,E]=maxcore(regressand,parameters,ma,tau)
%
% INPUTS:
% S
www.eeworm.com/read/245863/12776262
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/137160/13342332
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/314653/13562553
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/307760/13715438
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/136821/5851758
c motion_est.c
/*
* Motion estimation
* Copyright (c) 2000,2001 Fabrice Bellard.
* Copyright (c) 2002 Michael Niedermayer
*
*
* This library is free software; you can redistribute it and/or
* modify it unde
www.eeworm.com/read/493294/6400307
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
%