When “Optimal Filtering” Isn’t

Optimal filtering

This paper presents short summary about commonly used filters in macroeconomics. We consider Hodrick-Prescott filter, Butterworth filter, Ideal Bandpass filter, Baxter-King filter and Christiano-Fitzgerald filter. 1 The filtering problem Given raw data, {xt}t=1, we are interested in isolating component of xt, denoted by {yt}t=1, with period of oscillation between pl and pu, where 2 ≤ pl < pu < ...

Optimal cumulant domain filtering

This paper presents a new technique which exploits constrained optimization methods to derive optimal two dimensional filters in the cumulant domain for processing signals in non Gaussian noise, or signals with corrupting interferences which have non symmetrical probability density functions. The approach proposed here for enhancing signals in such noise is important, as increasingly practical ...

Optimal Seasonal Filtering

In this paper, I compare model-based and moving average-based approaches to seasonal adjustment. I propose an optimal moving average filter, designed to minimize the distance from a model-based filter. In simulations, I consider the accuracy of the alternative methods in estimating seasonal factors in a simple model. I find that the most reliable results are obtained either by the model-based a...

H2 Optimal Robust Filtering

an optimal similarity measure for collaborative filtering using firefly algorithm

recommender systems (rs) provide personalized recommendation according to user need by analyzing behavior of users and gathering their information. one of the algorithms used in recommender systems is user-based collaborative filtering (cf) method. the idea is that if users have similar preferences in the past, they will probably have similar preferences in the future. the important part of col...