{"id":140,"date":"2013-04-19T16:52:12","date_gmt":"2013-04-19T16:52:12","guid":{"rendered":"http:\/\/kourentzes.com\/forecasting\/?p=140"},"modified":"2016-08-15T06:19:05","modified_gmt":"2016-08-15T06:19:05","slug":"nemenyi-test","status":"publish","type":"post","link":"https:\/\/kourentzes.com\/forecasting\/2013\/04\/19\/nemenyi-test\/","title":{"rendered":"ANOM and Nemenyi tests"},"content":{"rendered":"

Code for the ANOM and Nemenyi tests for MatLab. Download here<\/a>.<\/p>\n

For a discussion of the two tests and the various ways to visualise the results look at this post<\/a>.<\/p>\n

Here are some examples, using the M3 results:<\/p>\n

>> anom(X,0.05,labels);\r\n<\/pre>\n<\/a>
\nThe models in red are significantly better than the average (solid line).<\/p>\n
For the Nemenyi test:<\/p>\n
>> nemenyi(X,1,'labels',labels,'colormap','hsv');\r\n<\/pre>\n<\/a>
\nThere is no evidence of significant differences for models joined by the vertical lines. Depending on the model we are considering, different groups can be formed. The groups are identified using the mean rank of a model \u00b1 the critical distance.
\nThere are several plotting options coded for the the nemenyi.m<\/em>. I have also put an option for changing the colourmap to better visualise the comparisons. A potentially useful option is to set:<\/p>\n
>> nemenyi(X,1,'labels',labels,'colormap','omcb');\r\n<\/pre>\nwhich gives you the MCB test with ordered models. These two tests use exactly the same statistic, although MCB compares only with the best model.
\n<\/a><\/p>\n
You may also be interested in this very nice visualisation of Nemenyi post-hoc test by Farshid Sepehrband available here<\/a>.<\/p>\n
Related Posts<\/H3>Tutorial for the nnfor R package<\/a><\/li>\n
Update for nnfor: reuse and retrain models<\/a><\/li>\n
MAPAx example for R<\/a><\/li>\n<\/ul><\/div>","protected":false},"excerpt":{"rendered":"Code for the ANOM and Nemenyi tests for MatLab. Download here. For a discussion of the two tests and the various ways to visualise the results look at this post. Here are some examples, using the M3 results: >> anom(X,0.05,labels); The models in red are significantly better than the average (solid line). For the Nemenyi\u2026 Read More »<\/a><\/span><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[11],"tags":[45,40,25],"_links":{"self":[{"href":"https:\/\/kourentzes.com\/forecasting\/wp-json\/wp\/v2\/posts\/140"}],"collection":[{"href":"https:\/\/kourentzes.com\/forecasting\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/kourentzes.com\/forecasting\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/kourentzes.com\/forecasting\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/kourentzes.com\/forecasting\/wp-json\/wp\/v2\/comments?post=140"}],"version-history":[{"count":0,"href":"https:\/\/kourentzes.com\/forecasting\/wp-json\/wp\/v2\/posts\/140\/revisions"}],"wp:attachment":[{"href":"https:\/\/kourentzes.com\/forecasting\/wp-json\/wp\/v2\/media?parent=140"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/kourentzes.com\/forecasting\/wp-json\/wp\/v2\/categories?post=140"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/kourentzes.com\/forecasting\/wp-json\/wp\/v2\/tags?post=140"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}