I'm wondering how to implement two-way clustering, as explained in Statistica documentation in R. Any help in this regard will be highly appreciated. Thanks
It's not clear to me whether the link you gave referenced standard clustering techniques for $n$ (individuals) by $k$ (variables) matrix of measures where we impose constraints on the resulting heatmap displays, or two-mode clustering or biclustering.
In the first approach, we could, for example,
Please, note that this is just a two-step process to conveniently display summary measures of association: clustering of rows (individuals or variables) and columns (individuals or variables) is done separately.
In the second approach (biclustering), that I'm inclined to favour, I only know one R package, biclust, that is greatly inspired for research in bioinformatics. Some pointers were also given in an earlier thread. (But there's even some papers in the psychometrics literature.) In this case, we need to put some constraints during clustering because we want to cluster both individuals and variables at the same time.
Again, you can display the resulting structure as heatmaps (see