We present an algorithm to estimate the parameters of a linear model in the presence of heteroscedastic noise, i.e., each data point having a different covariance matrix. The algor...
We develop a method to forecast stock keeping unit sales that is accurate, transparent and consistent in handling similar situations. We leverage the marketing literature to define...
Background: Most genomic data have ultra-high dimensions with more than 10,000 genes (probes). Regularization methods with L1 and Lp penalty have been extensively studied in survi...
Zhenqiu Liu, Dechang Chen, Ming Tan, Feng Jiang, R...
Linear discriminant analysis (LDA) is a popular method in pattern recognition and is equivalent to Bayesian method when the sample distributions of different classes are obey to t...
Zhen Lei, ShengCai Liao, Dong Yi, Rui Qin, Stan Z....
The Total Least Squares method is generalized in the context of the functional linear model. A smoothing splines estimator of the functional coefficient of the model is first prop...