In rugged mountain areas, the lateral aerodynamic force and lift caused by strong winds are main reasons for overturning of trains destruction buildings structures along railroad line. Therefore, it is important to build a wind alarm system line, reasonable accurate short-time forecast basis it. this research, two methods constructive function time-series decomposition proposed pre-process inpu...

When analyzing a financial asset, it is essential to study the trend of its time series. It also necessary examine evolution and activity over statistically analyze possible future behavior. Both retail institutional investors base their trading strategies on these analyses. One most used techniques series dynamic structure using auto-regressive models, simple moving average models (SMA), mixed...

El objetivo de esta investigación es analizar las relaciones internacionales entre países miembros la Comunidad Andina Naciones (CAN) y su efecto en el flujo comercio internacional Ecuador los miembros. Se consideran dos perspectivas. La primera analiza cambio significativo que pudieron tener exportaciones hacia CAN. segunda considera puedan importaciones provienen Para modelar series se un m...

The renewable energies prediction and particularly global radiation forecasting is a challenge studied by a growing number of research teams. This paper proposes an original technique to model the insolation time series based on combining Artificial Neural Network (ANN) and Auto-Regressive and Moving Average (ARMA) model. While ANN by its non-linear nature is effective to predict cloudy days, A...

Some concern has been expressed over the continuous low production from Marginal oil field. This problem ascribed to multitude of hindrances occasioned by nature earth formation in zone. Attempts ascertain character or complexion such problems have often eluded researchers and operators study adopts use auto-regressive time series model find out root cause mechanism that generate high output ma...

This paper develops a general asymptotic theory for the estimation of strictly stationary and ergodic time series models. Under simple conditions that are straightforward to check, we establish the strong consistency, the rate of strong convergence and the asymptotic normality of a general class of estimators that includes LSE, MLE, and some M-type estimators. As an application, we verify the a...

With the increasing competition in the telecommunications industry, the operators try their best to increase telecom income via various measures, one of which is to set an amount of income as a goal to make the encouragement. Since accurate forecast of income plays an important role in income target setting, this paper builds a time series Autoregressive Integrated Moving Average Model (ARIMA) ...

We investigate changes in the time series characteristics of postwar U.S. inflation. In a model-based analysis the conditional mean of inflation is specified by a long memory autoregressive fractionally integrated moving average process and the conditional variance is modelled by a stochastic volatility process. We develop a Monte Carlo maximum likelihood method to obtain efficient estimates of...

This study assesses the connection between money supply and economic growth in developing countries. The made use of time series data from National Bureau Statistics (NBS) Bank Tanzania. was looked at using Auto Regressive Distributed Lag Model (ARDL). demonstrates that overall, has a significant favorable effect on expansion. results demonstrate boosts underdeveloped nations. indicate that, wh...