代码搜索：SiGe HBT

找到约 79 项符合「SiGe HBT」的源代码

代码结果 79
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www.eeworm.com/read/449504/7502946

m bgwr.m

function results = bgwr(y,x,east,north,ndraw,nomit,prior); % PURPOSE: compute Bayesian geographically weighted regression % model: y = Xb(i) + e, e = N(0,sige*V), % b(i)
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www.eeworm.com/read/449504/7503083

m sar_g.m

function results = sar_g(y,x,W,ndraw,nomit,prior) % PURPOSE: Bayesian estimates of the spatial autoregressive model % y = rho*W*y + XB + e, e = N(0,sige*V), V = diag(v1,v2,...vn) %
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www.eeworm.com/read/492929/6414262

m tvp.m

function result = tvp(y,x,parm,info) % PURPOSE: time-varying parameter maximum likelihood estimation % y(t) = X(t)*B(t) + e(t), e(t) = N(0,sige^2) % B(t) = B(t-1) + v(t), v(t)
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www.eeworm.com/read/433502/7925604

cpp _b_tree.cpp

// _B_TREE.cpp: implementation of the C_B_TREE class. // ////////////////////////////////////////////////////////////////////// #include "stdafx.h" #include "tree.h" #include "_B_TREE.h" #if
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www.eeworm.com/read/449504/7502055

m scstd.m

function scale = scstd(y,nobs,nlag) % PURPOSE: determines bvar() function scaling factor using a % univariate AR model (called by bvar() only) %-----------------------------------------------
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www.eeworm.com/read/449504/7502124

m ridge.m

function results = ridge(y,x,theta) % PURPOSE: computes Hoerl-Kennard Ridge Regression %--------------------------------------------------- % USAGE: results = ridge(y,x,theta) % where: y = depende
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www.eeworm.com/read/449504/7502270

m optim2_d.m

% PURPOSE: An example using fmin function % % to solve a spatial autoregressive model maximum % likelihood problem %----------------------------
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www.eeworm.com/read/449504/7502810

m f2_sem.m

function llike = f2_sem(parm,y,x,W,detval); % PURPOSE: evaluates log-likelihood -- given ML parameters % spatial error model using sparse matrix algorithms % --------------------------------------
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www.eeworm.com/read/449504/7502843

m sac.m

function results = sac(y,x,W1,W2,info) % PURPOSE: computes general Spatial Model estimates % model: y = rho*W1*y + X*b + u, u = lam*W2*u + e % ---------------------------------------------------
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www.eeworm.com/read/449504/7502874

m mess_like.m

function out = mess_like(parm,ys,xs,ymat); % PURPOSE: evaluate the likelihood for the hessian function % MESS model % --------------------------------------------------- % USAGE: out = m
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