Random forest regression (RF) is an extremely popular tool for the analysis of high-dimensional data. Nonetheless, its benefits may be lessened in sparse settings, due to weak predictors, and a pre-estimation dimension reduction (targeting) step is required. We show that proper targeting...

Fire disturbance usually breaks the original forest succession trajectory and causes changes in forest composition in the boreal forests region of China. Predicting the process of post-fire mixed tree species regrowth dynamic is critical for understanding the effect of environmental conditions...

The challenge in the campaign contribution literature has been to overcome the simultaneous equation bias that is inherent in the vote-contribution relationship. This paper proposes a new method to overcome this bias. It examines behavior at different points of time and relates it to...

The challenge in the campaign contribution literature has been to overcome the simultaneous equation bias that is inherent in the vote-contribution relationship. This paper proposes a new method to overcome this bias. It examines behavior at different points of time and relates it to...

Existing methods for data interpolation or backdating are either univariate or based on a very limited number of series, due to data and computing constraints that were binding until the recent past. Nowadays large datasets are readily available, and models with hundreds of parameters are fastly...

In this paper we study the zero frequency spectral properties of fractionally cointegrated long memory processes and introduce a new frequency domain principal components estimator of the cointegration space and the factor loading matrix for the long memory factors. We find that for fractionally...

Existing methods for data interpolation or backdating are either univariate or based on a very limited number of series, due to data and computing constraints that were binding until the recent past. Nowadays large datasets are readily available, and models with hundreds of parameters are fastly...