Fan, Heckman and Wand proposed locally weighted kernel polynomial regression methods for generalized linear models and quasilikelihood functions. When the covariate variables are missing at random, we ...
We suggest a one-dimensional jump-detection algorithm based on local polynomial fitting for jumps in regression functions (zero-order jumps) or jumps in derivatives (first-order or higher-order jumps) ...
2. Gaussian filters : Kalman, Information... 3. Nonparametric filters: Histogram, Particle... III. Machine Learning 1. Neural Nets : perceptron, multi-layered ...
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