Open Access Original Research Article

Modeling of Economic Data using Bivariate MGARCH Models

Shakarho Udi Pepple, Isaac Didi Essi, Amos Emeka

Asian Journal of Probability and Statistics, Page 1-15
DOI: 10.9734/ajpas/2021/v13i230301

Aims: The aim of this study is to examine Economic data using the multivariate GARCH model.

Study design: The study used monthly data of Nigerian crude oil prices (dollar Per Barrel) and Consumer price Index

Methodology:  This work covers time series data on crude oil price and consumer price Index rural obtained from   Central bank of Nigeria (CBN)   from 2000 to 2019. To achieve the aim of the study, bivariate VECH and BEKK model were applied.

Results: The results confirmed that returns on economic data were correlated. Also, diagonal multivariate VECH model confirmed one of the properties that it must be ‘positive semi-definite’ and the BEKK also confirmed the volatility spillover effects among the economic data.

Conclusion: From the results obtained, it was confirmed that conditional variances depends only on own lags and own lagged square returns and conditional covariances depends only on own lags and own lagged cross products of returns. As for cross-volatility effects, past innovations in crude oil price have greatest influence on future volatility of returns on economic data. It was also confirmed that time varying covariance displays among these economic data and lower degree of persistence and based on Model selection criteria using the Akaike information criteria (AIC) diagonal VECH model is better fitted than the BEKK model.

Open Access Original Research Article

Topological Indices of Some New Graph Operations and Their Possible Applications

Abdu Qaid Saif Alameri, Mohammed Saad Yahya Al-Sharafi

Asian Journal of Probability and Statistics, Page 16-30
DOI: 10.9734/ajpas/2021/v13i230302

A chemical graph theory is a fascinating branch of graph theory which has many applications related to chemistry. A topological index is a real number related to a graph, as its considered a structural invariant. It’s found that there is a strong correlation between the properties of chemical compounds and their topological indices. In this paper, we introduce some new graph operations for the first Zagreb index, second Zagreb index and forgotten index "F-index". Furthermore, it was found some possible applications on some new graph operations such as roperties of molecular graphs that resulted by alkanes or cyclic alkanes.

Open Access Original Research Article

Evaluation and Comparison of Three Classes of Central Composite Designs

Fidelia Chinenye Kiwu-Lawrence, Lawrence Chizoba Kiwu, Desmond Chekwube Bartholomew, Chukwudi Paul Obite, Akanno Felix Chikereuba

Asian Journal of Probability and Statistics, Page 31-47
DOI: 10.9734/ajpas/2021/v13i230304

Three classes of Central Composite Design: Central Composite Circumscribed Design (CCCD), Central Composite Inscribed Design (CCID) and Central Composite Face-Centered Design (CCFD) in Response Surface Methodology (RSM) were evaluated and compared using the A-, D-, and G-efficiencies for factors, k, ranging from 3 to 10, with 0-5 centre points, in other to determine the performances of the designs under consideration. The results show that the CCDs (CCCD, CCFD and CCID) are at their best when the G-efficiency is employed for all the factors considered while the CCID especially behaves poorly when using the A- and D-efficiencies.

Open Access Original Research Article

Bayesian Inference on Regression Model with an Unknown Change Point

Oluwadare O Ojo

Asian Journal of Probability and Statistics, Page 48-55
DOI: 10.9734/ajpas/2021/v13i230305

In this work, we describe a Bayesian procedure for detection of change-point when we have an unknown change point in regression model. Bayesian approach with posterior inference for change points was provided to know the particular change point that is optimal while Gibbs sampler was used to estimate the parameters of the change point model. The simulation experiments show that all the posterior means are quite close to their true parameter values. The performance of this method is recommended for multiple change points.

Open Access Original Research Article

Modeling Eects of Climatic Variables on Tea Production in Kenya Using Linear Regression Model with Serially Correlated Errors

Consolata A. Muganda, Sewe Stanley, Winnie Onsongo

Asian Journal of Probability and Statistics, Page 56-75
DOI: 10.9734/ajpas/2021/v13i230306

Aims/ Objectives: To formulated a linear regression model to capture the relationship between tea production and climatic variables in terms of ARIMA.
Place and Duration of Study: Department of Mathematics and Actuarial Science, Catholic University of Eastern Africa, Nairobi, Kenya, between June 2019 and April 2021.
Methodology: The study used time-series data for mean annual temperature, mean annual rainfall, humidity, solar radiation, and NDVI, collected from six counties, namely Embu, Kakamega, Kisii, Kericho, Meru, and Nyeri.
Results: The study ndings noted that there is a presence of trend and seasonality for all the data. The scatter plot matrix for all the climatic variables for all the counties under the study indicated that tea production has a linear relationship with most climatic variables. Model t of the data indicated statistical signicance when tea production data is dierenced. A second linear model with tea production data deseasoned has mixed results in terms of a signicance
test. The variation of independent variables with tea production yielded very low values, suggesting that the data used has many variabilities.
Conclusion: The study ndings show the climatic variables can be used to forecast tea production.
Recommendation: Future studies may combine the analysis with other statistical modeling procedures such as the GARCH models.