Asian Research Journal of Mathematics 2021-05-14T04:27:05+00:00 Asian Research Journal of Mathematics Open Journal Systems <p style="text-align: justify;"><strong>Asian Research Journal of Mathematics (ISSN: 2456-477X)</strong> aims to publish high-quality papers (<a href="/index.php/ARJOM/general-guideline-for-authors">Click here for Types of paper</a>) in all areas of ‘Mathematics and Computer Science’. By not excluding papers on the basis of novelty, this journal facilitates the research and wishes to publish papers as long as they are technically correct and scientifically motivated. The journal also encourages the submission of useful reports of negative results. This is a quality controlled, OPEN peer-reviewed, open access INTERNATIONAL journal.</p> Comparison of the Performance of the SANN, SARIMA and ARIMA Models for Forecasting Quarterly GDP of Nigeria 2021-05-13T23:44:35+00:00 Chukwudike C. Nwokike Emmanuel W. Okereke <p>This research aimed at modelling and forecasting the quarterly GDP of Nigeria using the Seasonal Artificial Neural Network (SANN), SARIMA and Box-Jenkins models as well as comparing their predictive performance. The three models mentioned earlier were successfully fitted to the data set. Tentative architecture for the SANN was suggested by varying the number of neurons in the hidden layer while that of the input and output layer remained constant at 4. It was observed that the best architecture was when the hidden layer had 10 neurons and thus SANN (4-10-4) was chosen as the best. In fitting the ARIMA/SARIMA models, the Augmented Dickey Fuller (ADF) test was used to check for stationarity. Variance stabilization and Stationarity were achieved after logarithm transformation and first regular differencing. The ARIMA/SARIMA model with lowest AIC, BIC and HQIC values was chosen as the best amongst the competing models and fitted to the data. The adequacy of the fitted models was confirmed observing the correlogram of the residuals and the Ljung-Box Chi-Squared test result. The SANN model performed better than the SARIMA and ARIMA models as it had a Mean Squared Error value of 0.004 while SARIMA and ARIMA had mean squared errors of 0.527 and 0.705 respectively. It was concluded that the SANN which is a non-linear model be used in modelling the quarterly GDP of Nigeria. Hybrid models which combine the strength of individual models are recommended for further research.</p> 2021-05-10T11:33:34+00:00 ##submission.copyrightStatement## Estimation of the Residuals Entropy Function of Inverse Weibull Distribution Based on Generalized Type-II Hybrid Censored Samples 2021-05-14T04:27:05+00:00 Moshera A. M. Ahmad <p>Shannon’s entropy plays important role in the information theory. However, it can’t be applied to systems which have survived for some time. Therefore, the concept of residual entropy was developed. In this paper, the estimation of the entropy of a two-parameter inverse Weibull distribution based on the generalized type-II hybrid censored sample is considered. The Bayes estimator for the residual entropy of the Inverse Weibull distribution under the generalized type-II hybrid censored sample is given. Simulation experiments are conducted to see the effectiveness of the different estimators.</p> 2021-05-11T00:00:00+00:00 ##submission.copyrightStatement##