Time series cross-validation for lasso
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I am trying to estimate a lasso model using time series data and I would like to use cross-validation to select the lamda parameter. However, K-flod validation randomly shuffles the data and therefore it is not optimal in a time-series context; something like forward chaining would be more appropriate. I have no clue how to do this in matlab as the lasso or the cvpartition functions do not offer such option.