Estimation of conditional quantiles at very high or low tails is of interest in numerous
applications. Quantile regression provides a convenient and natural way of quantifying the …

Uncertainty in climate forcings causes significant uncertainty in estimating streamflow and
other land-surface fluxes in hydrologic model simulations. Earlier studies primarily analyzed …

Barnett, TP, and R. Preisendorfer, 1987: Origins and levels of monthly and seasonal forecast
skill for United States surface air temperatures determined by canonical correlation analysis …

Motivated by the problem of selecting representative portfolios for backtesting counterparty
credit risks, we propose a matching quantiles estimation (MQE) method for matching a target …

The General Circulation Model (GCM) simulation had shown potential in yielding long-term
statistical attributes of Indian precipitation and temperature which exhibit substantial inter …

There is a growing demand for multiple output prediction methods capable of both
minimizing residual errors and capturing the joint distribution of the response variables in a …

Analyzing the data collected from different sources requires unpaired data analysis to
account for the absence of correspondence between the random variable Y and the …

In the context of global climate change, the Qinghai-Tibetan plateau (QTP) has experienced
unprecedented changes in its local climate. While general circulation models (GCM) are …

Statistical bias correction techniques are commonly used in climate model projections to
reduce systematic biases. Among the several bias correction techniques, univariate linear …

Twenty years ago Breiman (2001) called to our attention a significant cultural division in
modeling and data analysis between the stochastic data models and the algorithmic models …