文件名称:KPMstats

  • 所属分类:
  • 金融证券系统
  • 资源属性:
  • [Matlab] [源码]
  • 上传时间:
  • 2012-11-26
  • 文件大小:
  • 89kb
  • 下载次数:
  • 0次
  • 提 供 者:
  • 李*
  • 相关连接:
  • 下载说明:
  • 别用迅雷下载,失败请重下,重下不扣分!

介绍说明--下载内容均来自于网络,请自行研究使用

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
相关搜索: kalman
kalman
matlab

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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~

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