𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Correlation estimation and time-series modeling for nonstationary processes

✍ Scribed by William A Gardner

Publisher
Elsevier Science
Year
1988
Tongue
English
Weight
773 KB
Volume
15
Category
Article
ISSN
0165-1684

No coin nor oath required. For personal study only.

πŸ“œ SIMILAR VOLUMES

Sequential estimation for time series re
Sequential estimation for time series regression models
✍ Takayuki Shiohama; Masanobu Taniguchi πŸ“‚ Article πŸ“… 2004 πŸ› Elsevier Science 🌐 English βš– 297 KB

Sequential procedures are proposed to estimate the regression parameters in a linear regression model with dependent residuals. The error process considered here is a linear process with unknown spectral density. The sequential point estimator for the regression parameters is based on the least-squa

Estimating and modeling space–time corre
Estimating and modeling space–time correlation structures
✍ L.De Cesare; D.E Myers; D Posa πŸ“‚ Article πŸ“… 2001 πŸ› Elsevier Science 🌐 English βš– 77 KB

In this paper, a class of product-sum covariance models has been introduced for estimating and modeling space-time correlation structures. It is shown how the coe cients of this class of models are related to the global sill and "partial" spatial and temporal sills; moreover, some constraints on the

Bayesian dynamic modelling for nonstatio
Bayesian dynamic modelling for nonstationary hydroclimatic time series forecasting along with uncertainty quantification
✍ D. Nagesh Kumar; Rajib Maity πŸ“‚ Article πŸ“… 2008 πŸ› John Wiley and Sons 🌐 English βš– 231 KB πŸ‘ 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,