Problem with big data (?) during computation of sequence distances using TraMineR

Question

I am trying to run an optimal matching analysis using TraMineR but it seems that I am encountering an issue with the size of the dataset. I have a big dataset of European co

Answer 1

An easy solution which often works well is to analyze a sample only of your data. For instance

employdat.sts <- employdat.sts[sample(nrow(employdat.sts),5000),]

would extract a random sample of 5000 sequences. Exploring such an important sample should be largely sufficient to find out the characteristics of your sequences, including their diversity.

To improve representativeness, you can even resort to some stratified sampling (e.g., by first or last state, or by some covariates available in your data set). Since you have the original data set at hand, you can fully control the random sampling design.

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Update

If clustering is the objective and you need a cluster membership for each individual sequence see https://stackoverflow.com/a/63037549/1586731