Takashi Ikeuchi

Hi @kitahara-neut, Thanks for your report. Please let me know what kind of error you get.

Hi @FTamas77 , The `m` is an array that we are creating to draw the true DAG, so we do not use it to run RESIT. Like the inputs and...

@FTamas77 One in the adjacency matrix represents an edge in the causal graph, while zero represents no edge. Edges denote causation rather than correlation. Because the relationship between variables is...

Hi, @pmisiakos This has already been fixed in issue #86. Please update to v1.8.0 or higher. ```bash pip install -U lingam ```

It seems to be a problem with graphviz. Similarly, Japanese label cannot be displayed in PDF, but can be displayed in SVG. ```python dot = make_dot(model.adjacency_matrix_, labels=['変数1', '変数2', '変数3']) dot.format...

Hi, @vdemchenko3. Thanks for reporting this problem. I'll fix this in v1.7.1, which will be released shortly.

Hi, @vdemchenko3 An issue with a similar problem was posted on the progressbar2 GitHub. https://github.com/wolph/python-progressbar/issues/276 I don't know why, but it seems that an older version of progressbar2 is being...

@Boyle-Coffee Thanks for using lingam. In [the paper](http://pages.cs.wisc.edu/~shao/stat992/zou2006.pdf), weights are defined as w=1/|beta|^gamma . Then, X**=X/w and beta*=beta**/w are defined. So, instead of dividing X by w, we multiply X...

Hi, @paullabonne . Thanks for reporting and analyzing this problem. As you pointed out, we have confirmed that the reference to the number of lags is incorrect when pruning edges....

Hi @paullabonne , I'm sorry, but I don't understand the points of the feedback. Could you please explain what code modifications are necessary? Thank you for the pull request! https://github.com/cdt15/lingam/pull/162