Results 21 to 30 of about 262 (135)

Forecasting Industrial Production Using Its Aggregated and Disaggregated Series or a Combination of Both: Evidence from One Emerging Market Economy

Econometrics, 2022
In this paper, we address whether using a disaggregated series or combining an aggregated and disaggregated series improves the forecasting of the aggregated series compared to using the aggregated series alone.
Diogo de Prince, Emerson Fernandes Marçal, Pedro L. Valls Pereira   +2 more
doaj   +1 more source

Automatic time series modeling and forecasting: A replication case study of forecasting real GDP, the unemployment rate and the impact of leading economic indicators

Cogent Economics & Finance, 2020
We test and report on time series modelling and forecasting using several US. Leading economic indicators (LEI) as an input to forecasting real US. GDP and the unemployment rate.
John Guerard, Dimitrios Thomakos, Foteini Kyriazi   +2 more
doaj   +1 more source

The price and income elasticities of natural gas demand in Azerbaijan: Is there room to export more?

Humanities & Social Sciences Communications, 2023
Natural gas is frequently introduced as a “transitional fuel”. Because burning natural gas emits less carbon dioxide emissions than burning either oil or coal.
Sarvar Gurbanov, Jeyhun I. Mikayilov, Shahriyar Mukhtarov, Shahin Maharramli   +3 more
doaj   +1 more source

Annihilators in Normal Autometrized Algebras [PDF]

Czechoslovak Mathematical Journal, 2001
The concepts of an annihilator and a relative annihilator in an autometrized l-algebra are introduced. It is shown that every relative annihilator in a normal autometrized l-algebra \(\mathcal{A}\) is an ideal of \(\mathcal{A}\) and every principal ideal of \(\mathcal{A}\) is an annihilator of \(\mathcal{A}\).
Ivan Chajda, Jiri Rachunek
openaire   +1 more source

SURE-Autometrics algorithm for model selection in multiple equations [PDF]

, 2016
The ambiguous process of model building can be explained by expert modellers due to their tacit knowledge acquired through research experiences.
Norhayati, Yusof
core   +1 more source

Evaluating Forecasts, Narratives and Policy Using a Test of Invariance

Econometrics, 2017
Economic policy agencies produce forecasts with accompanying narratives, and base policy changes on the resulting anticipated developments in the target variables.
Jennifer L. Castle, David F. Hendry, Andrew B. Martinez   +2 more
doaj   +1 more source

Sure (EM)-Autometrics: An Automated Model Selection Procedure with Expectation Maximization Algorithm Estimation Method (S/O 14925)

, 2021
Model selection is the process of choosing a model from a set of possible models. The model's ability to generalise means it can fit both current and future data. Despite numerous emergences of procedures in selecting models automatically, there has been
Kamarudin, Nur Azulia
core   +1 more source

Analysis of Fat Big Data Using Factor Models and Penalization Techniques: A Monte Carlo Simulation and Application

Axioms
This article assesses the predictive accuracy of factor models utilizing Partial·Least·Squares (PLS) and Principal·Component·Analysis (PCA) in comparison to autometrics and penalization techniques.
Faridoon Khan, Olayan Albalawi
doaj   +1 more source

Enhancing the Cloud Computing Performance by Labeling the Free Node Services as Ready‐To‐Execute Tasks

Journal of Electrical and Computer Engineering, Volume 2017, Issue 1, 2017., 2017
The huge bandwidth and hardware capacity form a high combination together which leads to a vigorous development in the Internet. On the other hand, different problems will come up during the use of the networks such as delay and node tasks load. These problems lead to degrade the network performance and then affect network service for users.
Radwan S. Abujassar, Moneef Jazzar, Marimuthu Karuppiah   +2 more
wiley   +1 more source

A Novel Approach to Forecasting After Large Forecast Errors

Journal of Forecasting, Volume 45, Issue 2, Page 837-849, March 2026.
ABSTRACT A sequence of increasingly large same‐sign 1‐step‐ahead forecast errors are most likely due to a sudden unexpected shift. Large forecast errors can be expensive, but also contain valuable information. Impulse indicators acting as intercept corrections to set forecasts back on track can be quickly tested for replacing outliers, a location shift
Jennifer L. Castle, Jurgen A. Doornik, David F. Hendry   +2 more
wiley   +1 more source