✦ LIBER ✦

Exponomial forecasts of nonstationary time series

✍ Scribed by Benjamin Kedem-Kimelfeld

Publisher: Elsevier Science
Year: 1976
Tongue: English
Weight: 204 KB
Volume: 54
Category: Article
ISSN: 0022-247X
DOI: 10.1016/0022-247x(76)90213-4

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Bayesian dynamic modelling for nonstatio

Bayesian dynamic modelling for nonstationary hydroclimatic time series forecasting along with uncertainty quantification

✍ D. Nagesh Kumar; Rajib Maity 📂 Article 📅 2008 🏛 John Wiley and Sons 🌐 English ⚖ 231 KB 👁 1 views

## Abstract Forecasting of hydrologic time series, with the quantification of uncertainty, is an important tool for adaptive water resources management. Nonstationarity, caused by climate forcing and other factors, such as change in physical properties of catchment (urbanization, vegetation change,

Nonstationary time series analysis of in

Nonstationary time series analysis of intramolecular energy transfer

✍ Lisa M. Finney; Angela Borrmann; Craig C. Martens 📂 Article 📅 1993 🏛 Elsevier Science 🌐 English ⚖ 589 KB

The dynamics of intramolecular energy transfer are investigated using an application of nonstationary time series methodology to the analysis of classical trajectory simulations. The approach is based on calculation of a joint time-frequency Wiper-Ville distribution from the evolving particle veloci

Forecasting non-normal time series

✍ A. L. Swift; G. J. Janacek 📂 Article 📅 1991 🏛 John Wiley and Sons 🌐 English ⚖ 979 KB

We look at the problem of forecasting time series which are not normally distributed. An overall approach is suggested which works both on simulated data and on real data sets. The idea is intuitively attractive and has the considerable advantage that it can readily be understood by nonspecialists.

The bias in time series volatility forec

The bias in time series volatility forecasts

✍ Louis H. Ederington; Wei Guan 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 137 KB

## Abstract By Jensen's inequality, a model's forecasts of the variance and standard deviation of returns cannot both be unbiased. This study explores the bias in GARCH type model forecasts of the standard deviation of returns, which we argue is the more appropriate volatility measure for most fina

Time series forecasts and extra-model in

Time series forecasts and extra-model information

✍ Alan Pankratz 📂 Article 📅 1989 🏛 John Wiley and Sons 🌐 English ⚖ 550 KB

Often a forecaster has supplementary information (e.g. field reports or forecasts from another source) that cannot be included directly in a time series model. Especially interesting are cases where this information is given at time intervals that are different from those of the time series model fo

Forecasting growth with time series mode

Forecasting growth with time series models

✍ Daniel Peña 📂 Article 📅 1995 🏛 John Wiley and Sons 🌐 English ⚖ 485 KB 👁 1 views

This paper compares the structure of three models for estimating future growth in a time series. It is shown that a regression model gives minimum weight to the last observed growth and maximum weight to the observed growth in the middle of the sample period. A first-order integrated ARIMA model, or