function?[varargout]?=?MTGP（hyp?inf?mean?cov?lik?x?y?xs?ys）
%?Gaussian?Process?inference?and?prediction.?The?gp?function?provides?a
%?flexible?framework?for?Bayesian?inference?and?prediction?with?Gaussian
%?processes?for?scalar?targets?i.e.?both?regression?and?binary
%?classification.?The?prior?is?Gaussian?process?defined?through?specification
%?of?its?mean?and?covariance?function.?The?likelihood?function?is?also
%?specified.?Both?the?prior?and?the?likelihood?may?have?hyperparameters
%?associated?with?them.
%
%?Two?modes?are?possible:?training?or?prediction:?if?no?test?cases?are
%?supplied?then?the?negative?log?marginal?likelihood?and?its?partial
%?derivatives?w.r.t.?the?hyperparameters?is?computed;?this?mode?is?used?to?fit
%?the?hyperparameters.?If?test?cases?are?given?then?the?test?set?predictive
%?probabilities?are?returned.?Usage:
%
%???training:?[nlZ?dnlZ??????????]?=?gp（hyp?inf?mean?cov?lik?x?y）;
%?prediction:?[ymu?ys2?fmu?fs2???]?=?gp（hyp?inf?mean?cov?lik?x?y?xs）;
%?????????or:?[ymu?ys2?fmu?fs2?lp]?=?gp（hyp?inf?mean?cov?lik?x?y?xs?ys）;
%
%?where:
%
%???hyp??????column?vector?of?hyperparameters
%???inf??????function?specifying?the?inference?method?
%???cov??????prior?covariance?function?（see?below）
%???mean?????prior?mean?function
%???lik??????likelihood?function
%???x????????n?by?D?matrix?of?training?inputs
%???y????????column?vector?of?length?n?of?training?targets
%???xs???????ns?by?D?matrix?of?test?inputs
%???ys???????column?vector?of?length?nn?of?test?targets
%
%???nlZ??????returned?value?of?the?negative?log?marginal?likelihood
%???dnlZ?????column?vector?of?partial?derivatives?of?the?negative
%???????????????log?marginal?likelihood?w.r.t.?each?hyperparameter
%???ymu??????column?vector?（of?length?ns）?of?predictive?output?means
%???ys2??????column?vector?（of?length?ns）?of?predictive?output?variances
%???fmu??????column?vector?（of?length?ns）?of?predictive?latent?means
%???fs2??????column?vector?（of?length?ns）?of?predictive?latent?variances
%???lp???????column?vector?（of?length?ns）?of?log?predictive?probabilities
%
%???post?????struct?representation?of?the?（approximate）?posterior
%????????????3rd?output?in?training?mode?or?6th?output?in?prediction?mode
%????????????can?be?reused?in?prediction?mode?gp（..?cov?lik?x?post?xs..）
%?
%?See?also?covFunctions.m?infMethods.m?likFunctions.m?meanFunctions.m.
%
%?Copyright?（c）?by?Carl?Edward?Rasmussen?and?Hannes?Nickisch?2013-01-21
if?nargin<7?||?nargin>9
??disp（‘Usage:?[nlZ?dnlZ??????????]?=?gp（hyp?inf?mean?cov?lik?x?y）;‘）
??disp（‘???or:?[ymu?ys2?fmu?fs2???]?=?gp（hyp?inf?mean?cov?lik?x?y?xs）;‘）
??disp（‘???or:?[ymu?ys2?fmu?fs2?lp]?=?gp（hyp?inf?mean?cov?lik?x?y?xs?ys）;‘）
??return
end

if?isempty（mean）?mean?=?{@meanZero};?end?????????????????????%?set?default?mean
if?ischar（mean）?||?isa（mean?‘function_handle‘）?mean?=?{mean};?end??%?make?cell
if?isempty（cov）?error（‘Covariance?function?cannot?be?empty‘）;?end??%?no?default
if?ischar（cov）??||

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????目錄???????????0??2014-03-28?05:01??MTGP?v1.4\cov\
?????文件?????????258??2014-02-12?17:16??MTGP?v1.4\cov\corr_2d.m
?????文件?????????142??2014-02-12?17:16??MTGP?v1.4\cov\corr_nd.m
?????文件????????2796??2014-03-09?11:13??MTGP?v1.4\cov\MTGP_covCC_chol_nD.m
?????文件????????3568??2014-03-09?11:15??MTGP?v1.4\cov\MTGP_covCC_chol_nD_mask.m
?????文件????????2329??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covMaterniso.m
?????文件????????2250??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covMaternisoU.m
?????文件????????3274??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covMaternisoU_shift.m
?????文件????????3954??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covMaternisoU_shift_mask.m
?????文件????????1963??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covNoise.m
?????文件????????1860??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covPeriodiciso.m
?????文件????????1816??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covPeriodicisoU.m
?????文件????????1783??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covPeriodicisoUU.m
?????文件????????2857??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covPeriodicisoUU_shift.m
?????文件????????3538??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covPeriodicisoUU_shift_mask.m
?????文件????????2415??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covProd.m
?????文件????????4150??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covQPMisoUU_shift.m
?????文件????????4784??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covQPMisoUU_shift_mask.m
?????文件????????3571??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covQPSisoUU_shift.m
?????文件????????4249??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covQPSisoUU_shift_mask.m
?????文件????????2149??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covRQiso.m
?????文件????????1984??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covRQisoU.m
?????文件????????4302??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covSEconU.m
?????文件????????1882??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covSEiso.m
?????文件????????1765??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covSEisoU.m
?????文件????????2870??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covSEisoU_shift.m
?????文件????????3554??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covSEisoU_shift_mask.m
?????文件????????3388??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covSEisoU_shift_nD.m
?????文件????????2162??2014-02-12?17:16??MTGP?v1.4\cov\MTGP_covSum.m
?????目錄???????????0??2014-03-28?04:59??MTGP?v1.4\example\
?????目錄???????????0??2014-03-28?05:02??MTGP?v1.4\example\convolution\
............此處省略48個文件信息