𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Time series prediction model for sequential learning

✍ Scribed by Manabu Gouko; Yoshihiro Sugaya; Hirotomo Aso

Publisher
John Wiley and Sons
Year
2007
Tongue
English
Weight
384 KB
Volume
90
Category
Article
ISSN
8756-663X

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Misspecified prediction for time series
Misspecified prediction for time series
✍ In-Bong Choi; Masanobu Taniguchi 📂 Article 📅 2001 🏛 John Wiley and Sons 🌐 English ⚖ 205 KB

## Abstract Let {__X__~__t__~} be a stationary process with spectral density __g__(λ).It is often that the true structure __g__(λ) is not completely specified. This paper discusses the problem of misspecified prediction when a conjectured spectral density __f__~θ~(λ), θ∈Θ, is fitted to __g__(λ). Th

On multistep prediction error methods fo
On multistep prediction error methods for time series models
✍ Petre Stoica; Arye Nehorai 📂 Article 📅 1989 🏛 John Wiley and Sons 🌐 English ⚖ 574 KB

Multistep prediction error methods for linear time series models are considered from both a theoretical and a practical standpoint. The emphasis is on autoregressive moving-average (ARMA) models for which a multistep prediction error estimation method (PEM) is developed. The results of a Monte Carlo

Time-simultaneous prediction band for a
Time-simultaneous prediction band for a time series
✍ Dag Kolsrud 📂 Article 📅 2007 🏛 John Wiley and Sons 🌐 English ⚖ 297 KB

## Abstract I propose principles and methods for the construction of a time‐simultaneous prediction band for a univariate time series. The methods are entirely based on a learning sample of time trajectories, and make no parametric assumption about its distribution. Hence, the methods are general a

Predictive models for ground ozone and n
Predictive models for ground ozone and nitrogen dioxide time series
✍ Monique Graf-Jaccottet; Marc-Henri Jaunin 📂 Article 📅 1998 🏛 John Wiley and Sons 🌐 English ⚖ 241 KB 👁 1 views

Predictive models are built for the mean ground concentration of ozone and nitrogen dioxide on data consisting of 5 years of daily averages. We ®nd the smallest averaging time over which a model with a deterministic trend and an autoregressive error distribution passes a number of statistical tests.

A space–time model for seasonal hurrican
A space–time model for seasonal hurricane prediction
✍ Thomas H. Jagger; Xufeng Niu; James B. Elsner 📂 Article 📅 2002 🏛 John Wiley and Sons 🌐 English ⚖ 180 KB

## Abstract A space–time count process model is explained and applied to annual North Atlantic hurricane activity. The model uses the best‐track data set of historical hurricane positions and intensities, together with climate variables, to determine local space–time coefficients of a right‐truncat