Temporal smoothing - A step forward for time-spectral methods

Moving Forward One Step at a Time

Peripheral arterial disease (PAD) is a common disorder and a major cause of morbidity and mortality.1 The most severely affected patients, with rest pain, ulcerations, or gangrene, are given a diagnosis of critical limb ischemia (CLI). These patients have a particularly poor prognosis, with high rates of limb amputation and mortality. Despite improvements in medical therapy for atherosclerosis ...

One step forward

Smoothing Methods for Histogram-valued Time Series

We adapt smoothing methods to histogram-valued time series (HTS) by introducing a barycentric histogram that emulates the "average" operation, which is the key to any smoothing filter. We show that, due to its linear properties, only the Mallows-barycenter is acceptable if we wish to preserve the essence of any smoothing mechanism. We implement a barycentric exponential smoothing to forecast th...

A Comparison Between Time Series, Exponential Smoothing, and Neural Network Methods To Forecast GDP of Iran

Two-step Smoothing Estimation of the Time-variant Parameter with Application to Temperature Data

‎In this article‎, ‎we develop two nonparametric smoothing estimators for parameter of a time-variant parametric model‎. ‎This parameter can be from any parametric family or from any parametric or semi-parametric regression model‎. ‎Estimation is based on a two-step procedure‎, ‎in which we first get the raw estimate of the parameter at a set of disjoint time...