Two-stage clustering in R 
*

*Is it possible to do 2-stage cluster analysis in R?

*Can anybody provide me resource on it?

 A: The closest package that I can think of is birch, but it is not available on CRAN anymore so you have to get the source and install it yourself (R CMD install birch_1.1-3.tar.gz works fine for me, OS X 10.6 with R version 2.13.0 (2011-04-13)). It implements the original algorithm described in 

Zhang, T. and Ramakrishnan, R. and
  Livny, M. (1997). BIRCH: A New Data
  Clustering Algorithm and Its
  Applications. Data Mining and
  Knowledge Discovery, 1, 141-182.

which relies on cluster feature tree, as does SPSS TwoStep (I cannot check, though). There's a possibility of using the k-means algorithm to perform clustering on birch object (kmeans.birch()), that is partition the subclusters into k groups such that the sum of squares of all the points in each subcluster to the assigned cluster centers is minimized.
A: Maybe this also can help: https://cran.r-project.org/web/packages/prcr/

Provides an easy-to-use yet adaptable set of tools to conduct person-center analysis using a two-step clustering procedure. As described in Bergman and El-Khouri (1999) doi:10.1002/(SICI)1521-4036(199910)41:6%3C753::AID-BIMJ753%3E3.0.CO;2-K, hierarchical clustering is performed to determine the initial partition for the subsequent k-means clustering procedure.

A: If you are looking for something akin to a 2-step, have you considered looking into Self Organizing Maps. I think it is based on similar (but not the same) principle as 2-step.
