文件名称:KPMstats
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非常好的MATLAB-KALMAN工具包，KPMstats is a directory of miscellaneous statistics functions written by
Kevin Patrick Murphy and various other people-MATLAB-KALMAN very good kit, KPMstats is a directory of miscellaneous statistics functions written byKevin Patrick Murphy and various other people
Kevin Patrick Murphy and various other people-MATLAB-KALMAN very good kit, KPMstats is a directory of miscellaneous statistics functions written byKevin Patrick Murphy and various other people
(系统自动生成,下载前可以参看下载内容)
下载文件列表
KPMstats
........\#chisquared_histo.m#
........\#clg_Mstep.m#
........\#clg_Mstep_simple.m#
........\#condGaussToJoint.m#
........\#convertBinaryLabels.m#
........\#KLgauss.m#
........\#linear_regression.m#
........\#logist2Apply.m#
........\#logist2ApplyRegularized.m#
........\#logist2FitRegularized.m#
........\#mixgauss_classifier_train.m#
........\#mixgauss_em.m#
........\#weightedRegression.m#
........\beta_sample.m
........\chisquared_histo.m
........\chisquared_histo.m~
........\chisquared_prob.m
........\chisquared_readme.txt
........\chisquared_table.m
........\clg_Mstep.m
........\clg_Mstep_simple.m
........\clg_Mstep_simple.m~
........\clg_prob.m
........\condGaussToJoint.m
........\condGaussToJoint.m~
........\condgaussTrainObserved.m
........\condgauss_sample.m
........\cond_indep_fisher_z.m
........\convertBinaryLabels.m
........\convertBinaryLabels.m~
........\CVS
........\...\Entries
........\...\Entries.Extra
........\...\Repository
........\...\Root
........\cwr_demo.m
........\cwr_em.m
........\cwr_predict.m
........\cwr_prob.m
........\cwr_readme.txt
........\cwr_test.m
........\dirichlet_sample.m
........\distchck.m
........\eigdec.m
........\est_transmat.m
........\fit_paritioned_model_testfn.m
........\fit_partitioned_model.m
........\gamma_sample.m
........\gaussian_prob.m
........\gaussian_sample.m
........\KLgauss.m
........\linear_regression.m
........\logist2.m
........\logist2Apply.m
........\logist2ApplyRegularized.m
........\logist2ApplyRegularized.m~
........\logist2Fit.m
........\logist2FitRegularized.m
........\logist2FitRegularized.m~
........\logistK.m
........\logistK_eval.m
........\marginalize_gaussian.m
........\matrix_normal_pdf.m
........\matrix_T_pdf.m
........\mc_stat_distrib.m
........\mixgauss_classifier_apply.m
........\mixgauss_classifier_train.m
........\mixgauss_em.m
........\mixgauss_init.m
........\mixgauss_Mstep.m
........\mixgauss_prob.m
........\mixgauss_prob_test.m
........\mkPolyFvec.m
........\mk_unit_norm.m
........\multinomial_prob.m
........\multinomial_sample.m
........\normal_coef.m
........\partial_corr_coef.m
........\parzen.m
........\parzenC.c
........\parzenC.dll
........\parzenC.mexglx
........\parzenC_test.m
........\parzen_fit_select_unif.m
........\pca.m
........\README.txt
........\rndcheck.m
........\sample.m
........\sample_discrete.m
........\sample_gaussian.m
........\standardize.m
........\student_t_logprob.m
........\student_t_prob.m
........\unif_discrete_sample.m
........\weightedRegression.m
........\weightedRegression.m~
........\#chisquared_histo.m#
........\#clg_Mstep.m#
........\#clg_Mstep_simple.m#
........\#condGaussToJoint.m#
........\#convertBinaryLabels.m#
........\#KLgauss.m#
........\#linear_regression.m#
........\#logist2Apply.m#
........\#logist2ApplyRegularized.m#
........\#logist2FitRegularized.m#
........\#mixgauss_classifier_train.m#
........\#mixgauss_em.m#
........\#weightedRegression.m#
........\beta_sample.m
........\chisquared_histo.m
........\chisquared_histo.m~
........\chisquared_prob.m
........\chisquared_readme.txt
........\chisquared_table.m
........\clg_Mstep.m
........\clg_Mstep_simple.m
........\clg_Mstep_simple.m~
........\clg_prob.m
........\condGaussToJoint.m
........\condGaussToJoint.m~
........\condgaussTrainObserved.m
........\condgauss_sample.m
........\cond_indep_fisher_z.m
........\convertBinaryLabels.m
........\convertBinaryLabels.m~
........\CVS
........\...\Entries
........\...\Entries.Extra
........\...\Repository
........\...\Root
........\cwr_demo.m
........\cwr_em.m
........\cwr_predict.m
........\cwr_prob.m
........\cwr_readme.txt
........\cwr_test.m
........\dirichlet_sample.m
........\distchck.m
........\eigdec.m
........\est_transmat.m
........\fit_paritioned_model_testfn.m
........\fit_partitioned_model.m
........\gamma_sample.m
........\gaussian_prob.m
........\gaussian_sample.m
........\KLgauss.m
........\linear_regression.m
........\logist2.m
........\logist2Apply.m
........\logist2ApplyRegularized.m
........\logist2ApplyRegularized.m~
........\logist2Fit.m
........\logist2FitRegularized.m
........\logist2FitRegularized.m~
........\logistK.m
........\logistK_eval.m
........\marginalize_gaussian.m
........\matrix_normal_pdf.m
........\matrix_T_pdf.m
........\mc_stat_distrib.m
........\mixgauss_classifier_apply.m
........\mixgauss_classifier_train.m
........\mixgauss_em.m
........\mixgauss_init.m
........\mixgauss_Mstep.m
........\mixgauss_prob.m
........\mixgauss_prob_test.m
........\mkPolyFvec.m
........\mk_unit_norm.m
........\multinomial_prob.m
........\multinomial_sample.m
........\normal_coef.m
........\partial_corr_coef.m
........\parzen.m
........\parzenC.c
........\parzenC.dll
........\parzenC.mexglx
........\parzenC_test.m
........\parzen_fit_select_unif.m
........\pca.m
........\README.txt
........\rndcheck.m
........\sample.m
........\sample_discrete.m
........\sample_gaussian.m
........\standardize.m
........\student_t_logprob.m
........\student_t_prob.m
........\unif_discrete_sample.m
........\weightedRegression.m
........\weightedRegression.m~