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Estimating High Dimensional Monotone Index Models by Iterative Convex Optimization1
For such monotone index models with increasing dimension, we propose to use a new class of estimators based on batched gradient descent (BGD) involving nonparametric methods such as kernel estimation or sieve estimation, and study their asymptotic properties.
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