Several methods for the analysis of nonlinear time series models have been proposed. As in linear autoregressive models the main problems are model identification, estimation and prediction. A boosting method is proposed that performs model identification and estimation simultaneously within the...

The use of the multinomial logit model is typically restricted to applications with few predictors, because in high-dimensional settings maximum likelihood estimates tend to deteriorate. A sparsity-inducing penalty is proposed that accounts for the special structure of multinomial models by...