Xiaoyan Wang

Tkanks for your kind reply! I would be glad and honored to be an alpha tester! Thanks for your suggestions! I think I'd try other methods to reach the optimal...

Great! Thanks!

I mean constructing a random network using parameters from our empirical network (like count of nodes, edges and so on). Here is an example that might be vivid (https://mp.weixin.qq.com/s?__biz=MzIxNzc1Mzk3NQ==&mid=2247484753&idx=1&sn=8b00273dfee2478478d43fbbc8da7bf3&chksm=97f5b549a0823c5f673d77006ace7641cbb93539537483e6fb15243b37187498573482f3b787&token=1817505529&lang=zh_CN&scene=21#wechat_redirect).

Thanks! Could we further get results like clustering coefficient, average path length rand and other network parameters according to every run of the random network, which may help us to...

In my own dataset, I called t1 as tmp, but it returns as follows. Is it possible to be more flexible when defining our object?  I guess the error...

It works! Thank you for your kind help!

Thanks for your reply! However I am still confused about the response to the question 3. Does it mean the cormat object generated after lioness(dat, netFun) was a weighted correlation...

Thanks for your kind reply! I would contact you by the website~

Great! I got it. Thanks!