function?[FHQRinitx?initV]?=?AR_to_SS（coef?C?y）
%
%?Convert?a?vector?auto-regressive?model?of?order?k?to?state-space?form.
%?[FHQR]?=?AR_to_SS（coef?C?y）
%?
%?X（i）?=?A（1）?X（i-1）?+?...?+?A（k）?X（i-k+1）?+?v?where?v?~?N（0?C）
%?and?A（i）?=?coef（::i）?is?the?weight?matrix?for?i?steps?ago.
%?We?initialize?the?state?vector?with?[y（:k）‘?...?y（:1）‘]‘?since
%?the?state?vector?stores?[X（i）?...?X（i-k+1）]‘?in?order.

[s?s2?k]?=?size（coef）;?%?s?is?the?size?of?the?state?vector
bs?=?s?*?ones（1k）;?%?size?of?each?block

F?=?zeros（s*k）;
for?i=1:k
???F（block（1bs）?block（ibs））?=?coef（::i）;
end
for?i=1:k-1
??F（block（i+1bs）?block（ibs））?=?eye（s）;
end

H?=?zeros（1*s?k*s）;
%?we?get?to?see?the?most?recent?component?of?the?state?vector?
H（block（1bs）?block（1bs））?=?eye（s）;?
%for?i=1:k
%??H（block（1bs）?block（ibs））?=?eye（s）;
%end

Q?=?zeros（k*s）;
Q（block（1bs）?block（1bs））?=?C;

R?=?zeros（s）;

initx?=?zeros（k*s?1）;
for?i=1:k
??initx（block（ibs））?=?y（:?k-i+1）;?%?concatenate?the?first?k?observation?vectors
end

initV?=?zeros（k*s）;?%?no?uncertainty?about?the?state?（since?perfectly?observable）

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----

?????文件????????117??2009-03-26?16:53??KalmanAll\Kalman\aaa.asv

?????文件???????1107??2002-05-29?08:59??KalmanAll\Kalman\AR_to_SS.m

?????文件????????425??2002-05-29?08:59??KalmanAll\Kalman\convert_to_lagged_form.m

?????文件????????354??2002-05-29?08:59??KalmanAll\Kalman\ensure_AR.m

?????文件???????1045??2002-05-29?08:59??KalmanAll\Kalman\eval_AR_perf.m

?????文件???????3005??2009-03-26?16:53??KalmanAll\Kalman\kalman_filter.asv

?????文件???????3007??2009-03-26?20:29??KalmanAll\Kalman\kalman_filter.m

?????文件???????2392??2002-11-01?16:32??KalmanAll\Kalman\kalman_forward_backward.m

?????文件???????1584??2002-05-29?08:59??KalmanAll\Kalman\kalman_smoother.m

?????文件???????1872??2009-03-26?20:23??KalmanAll\Kalman\kalman_update.asv

?????文件???????1876??2009-03-26?20:24??KalmanAll\Kalman\kalman_update.m

?????文件???????1022??2002-10-23?08:17??KalmanAll\Kalman\learning_demo.m

?????文件????????819??2002-05-29?08:59??KalmanAll\Kalman\learn_AR.m

?????文件????????687??2002-05-29?08:59??KalmanAll\Kalman\learn_AR_diagonal.m

?????文件???????5515??2006-08-24?14:37??KalmanAll\Kalman\learn_kalman.m

?????文件????????485??2004-06-07?07:39??KalmanAll\Kalman\README.txt

?????文件????????535??2003-01-18?13:47??KalmanAll\Kalman\README.txt~

?????文件???????2039??2009-03-27?11:51??KalmanAll\Kalman\sample_lds.asv

?????文件???????2039??2009-03-27?11:53??KalmanAll\Kalman\sample_lds.m

?????文件???????1199??2002-05-29?08:59??KalmanAll\Kalman\smooth_update.m

?????文件????????579??2002-05-29?08:59??KalmanAll\Kalman\SS_to_AR.m

?????文件?????????28??2009-03-27?11:30??KalmanAll\Kalman\testKalman.m

?????文件???????1976??2009-03-25?17:51??KalmanAll\Kalman\tracking_demo.asv

?????文件???????2010??2009-03-30?16:21??KalmanAll\Kalman\tracking_demo.m

?????文件????????267??2005-05-03?13:08??KalmanAll\KPMstats\#histCmpChi2.m#

?????文件???????1955??2005-04-25?19:29??KalmanAll\KPMstats\beta_sample.m

?????文件????????199??2005-04-25?19:29??KalmanAll\KPMstats\chisquared_histo.m

?????文件???????1326??2005-04-25?19:29??KalmanAll\KPMstats\chisquared_prob.m

?????文件???????1389??2005-04-25?19:29??KalmanAll\KPMstats\chisquared_readme.txt

?????文件???????2127??2005-04-25?19:29??KalmanAll\KPMstats\chisquared_table.m

............此處省略577個文件信息