The objective of this paper is to apply the Translog Stochastic Frontier production model (SFA) and Data Envelopment Analysis (DEA) to estimate efficiencies over time and the Total Factor Productivity (TFP) growth rate for Bangladeshi rice crops (Aus, Aman and Boro) throughout the most recent data available comprising the period 1989-2008. Results indicate that technical efficiency was observed...

Problem statement: Network traffic prediction plays a vital role in the optimal resource allocation and management in computer networks. This study introduces an ARIMA based model augmented by Adaptive Linear Prediction (ALP) for the real time prediction of VBR video traffic. The synergy of the two can successfully address the challenges in traffic prediction such as accuracy in prediction, res...

This paper considers univariate online electricity demand forecasting for lead times from a half-hour-ahead to a day-ahead. A time series of demand recorded at half-hourly intervals contains more than one seasonal pattern. A within-day seasonal cycle is apparent from the similarity of the demand profile from one day to the next, and a within-week seasonal cycle is evident when one compares the ...

Objectives Using Canadian mortality data from 1974 to 1995, this article examines seasonal and daily patterns of death by cause. Data source Death records were extracted from the Canadian Vital Statistics Data Base, which is compiled from information provided to Statistics Canada by the Vital Statistics Registries in each province and territory. Analytical techniques Components of the time seri...

We show that many time series data are governed by Geometric Brownian Motion (GBM) law. This motivates us to propose a procedure of time series model building for autocorrelated process control that might consist of two steps. First, we test whether the process data are governed by GBM law. If it is affirmative, the appropriate model is directly given by the properties of that law. Otherwise, w...

Abstract: This paper proposed a new method to estimate the missing data by using the filtering process. We used datasets without missing data and randomly missing data to evaluate the new method of estimation by using the Box Jenkins modeling technique to predict monthly average rainfall for site 5504035 Lahar Ikan Mati at Kepala Batas, P. Pinang station in Malaysia. The rainfall data was colle...

Inflation is one of the most widely tested economic variables both theoretically and empirically. Stable inflation a sign that sustainable growth provides benefits for improving people's welfare. This study aims to analyze impact Covid-19 on volatility in Indonesian. The method used this ARIMA model. results are ARMA (1.1.0) model suitable testing Indonesia. Forecasting show over next 5 months ...

this paper attempts to compare the forecasting performance of the arima model and hybrid arma-garch models by using daily data of the iran’s exchange rate against the u.s. dollar (irr/usd) for the period of 20 march 2014 to 20 june 2015. the period of 20 march 2014 to 19 april 2015 was used to build the model while remaining data were used to do out of sample forecasting and check the forecasti...

This study examines the forecasting performance of Adaptive Neuro Fuzzy Inference System(ANFIS) compared in comparison to statistical autoregressive integrated moving average (ARIMA) and the artificial neural network (ANN) model in forecasting of rice yield production.. To assess the effectiveness of these models, we used 9 years of time series records for rice yield data in Malaysia from 1995 ...