Median-Unbiased Optimal Smoothing and Trend Extraction

Median-Unbiased Optimal Smoothing and Trend Extraction

Optimal and Unbiased FIR Filtering in Discrete Time State Space with Smoothing and Predictive Properties

We address p-shift finite impulse response optimal (OFIR) and unbiased (UFIR) algorithms for predictive filtering (p > 0), filtering (p = 0), and smoothing filtering (p < 0) at a discrete point n over N neighboring points. The algorithms were designed for linear time-invariant state-space signal models with white Gaussian noise. The OFIR filter self-determines the initial mean square state func...

COMPUTING MEDIAN UNBIASED ESTIMATES IN MACROECONOmTRIC MODELS

A stochastic simulation procedure is proposed in this papa for obtaining median unbiased (Mu) estimates in macroeconometric models. MU estimates are computed for lagged dependent variable (LDV) coefficients in 18 equations of a macroeconometric model. The 2SLS bias for a coefficient, defined as the difference between the 2SLS estimate and the MU estimate, is on average smaller in absolute value...

Weighted Repeated Median Smoothing and Filtering

Damped Trend Exponential Smoothing: Prediction and Control

Damped trend exponential smoothing models have gained importance in empirical studies due to their remarkable forecasting performance. This paper derives their theoretical forecast error variance, based on the implied ARIMA model, as algebraic function of the structural parameters. As a consequence, the minimum mean squared error (MMSE) forecasts as well as the h-step ahead theoretical forecast...