Md. Abu Shahin

Rajshahi University, Statistics, Graduate Student

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Phone: 01712437768
Address: Md. Abu Shahin
C/O- Md. Abdul Quddus
Village: Hazrahati
Post Office: Hatshira
Thana: Kazipur,District: Sirajgonj
Country: Bangladesh

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Vector Autoregression (VAR) Modeling and Forecasting of Temperature, Humidity, and Cloud Coverage

Computational Intelligence Techniques in Earth and Environmental Sciences, 2014

Time Series Model Building and Forecasting on Maximum Temperature Data

Computational Intelligence Techniques in Earth and Environmental Sciences, 2014

TIME SERIES ANALYSIS, MODELING AND FORECASTING OF CLIMATE VARIABLE RAINFALL: A CASE STUDY OF RAJSHAHI DISTRICT IN BANGLADESH

by Md. Abu Shahin and Md. Monimul Huq

The purpose of the present study was to investigate the time series components, and to build an a... more The purpose of the present study was to investigate the time series components, and to build an appropriate model to forecasttherainfall of Rajshahi district in Bangladesh using the monthly rainfall data over January, 1975 to June, 2012 collected from Bangladesh meteorological department.The statistical software R with the packages 'forecast' and 'zyp' was used for whole analysis. The descriptive statistics of rainfall showed high fluctuation from their mean, positively skewed and platykurtic curve. The time series rainfall data was decomposedinto stochastic trend, seasonal variations and random movements. The yearly rainfall data showed decreasing trend by 11.25 mm/year. The moving average smoothing of monthly rainfall intended to be decreased over May, 2007 to June, 2012. But, after first seasonal difference, the rainfall data became stationary and that wasconformed using appropriate tests. The SARIMA(0, 0, 0)(4, 1, 0) 12 model was found as best model on the basis ofdiagnostic test, stability and reliability. The forecasted values from July, 2012 to December, 2025 divulged adecreasing pattern that may be a threat to the cultivators as well as to the nature as a whole.

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Analysis of Volatility and Forecasting General Index of Dhaka Stock Exchange

The purpose of the present study is to empirically examine the performance o f d ifferent kinds o... more The purpose of the present study is to empirically examine the performance o f d ifferent kinds of volatility modeling and their forecasting performance for the general index of an emerging stock market, namely Dhaka Stock Exchange fro m the period December 06, 2010 to March 12, 2013. We main ly used Box-Jenkins modeling strategy thereafter the volatility model. The descriptive statistics, correlogram, unit root test, ARMA, ARCH, GA RCH, TARCH, EGA RCH and several model selection criteria are used in this study. The Butterworth filter is used for removing the noise of the re turn series of general index. All the parameters in this study are estimated through Maximu m Likelihood method. The descriptive statistics show general index decrease slightly overtime with positively skewed and leptokurtic. The return series fo llo ws ARMA(1,1) model with volatility provide evidence of the superiority of GA RCH(1,1) and GARCH(2,1) over the all order of other GA RCH models. Finally, we found that the fitted model on filtered general index of Dhaka Stock Exchange are ARMA(1,1) with GA RCH(1, 1) and GA RCH(2,1) model. Th is model can be used for future policy imp lication through its accurate forecast.

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An Extension of Generalized Triphasic Logistic Human Growth Model

The purpose of the present study was to establish an extension of generalized tri-phasic logistic... more The purpose of the present study was to establish an extension of generalized tri-phasic logistic human growth model. This model was applied through the higher dimensional growth process. Bayesian method of estimation was applied to estimate the parameters of the model. Principal component regression method was applied when there was a problem of multicollinearity in the model. The biological characteristics of the human growth process were extracted from the velocity and acceleration curve using gradient vector and Hessian matrix.

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