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Edward Akurugu

Biographic Data

ID6891631
NAMEEdward Akurugu
GIVEN NAMESEdward
FAMILY NAMEAkurugu
SIGNATUREAKURUGU E
AFFILIATIONSUniversity for Development Studies
ORCID0009-0000-4550-0541
VERIFIEDYes
TOTAL WORKS3
TOTAL CITATIONS0
WORKS AS AUTHOR3
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2022
LATEST PUBLICATION YEAR2023
H-INDEX0
  • Modelling Factors Affecting Internally Generated Funds of the Tamale Metropolitan Assembly of Ghana Using Multivariate Analysis Techniques

    Saaka Takora, Edward Akurugu et al.•ARTICLE•Statistics Politics and Policy•2023

    The study was carried out to model factors that affect the Internally Generated Funds of the Tamale Metropolitan Assembly using Factor and Confirmatory Factor analysis. The study involved 403 categories of respondents using probability and non-probability sampling techniques. The results from the Factor analysis confirmed a four-factor structure model to accurately represent the observed data without substantial loss of information. The Factor an…

  • Bayesian Switching Volatility Models for Analysing Stock Returns in Ghana

    Edward Akurugu, Irene Dekomwine Angbing et al.•ARTICLE•Statistics Politics and Policy•2022•References: 1

    The goal of this research was to use Bayesian switching volatility models to model the stock returns of the GCB, bank in Ghana. Monthly stock prices of GCB bank for the period of 138 months were used for the study. The two-state Markov-Switching GARCH models were used in the study to determine the best model for modelling and forecasting the stock returns. The Deviance Information Criteria was considered when selecting the best model. Based on th…

  • Tweedie Regression Analysis of Determinants of Birth Weight in Navrongo

    Emmanuel N-yambi Tegee, Edward Akurugu et al.•ARTICLE•Statistics Politics and Policy•2022•References: 1

    The study modelled and investigated the determinants of infant birth weight by considering maternal and infant factors as predictors. Monthly data spanning for a period of 37 months were obtained from the Navrongo Health Research Centre of the Navrongo Municipality of the Upper East region of Ghana. In modelling the birth weight of infants, the Tweedie regression model and its counterparts of exponential families (Gaussian, Gamma and inverse Gaus…

No prominent works on this page.

  • Bayesian Switching Volatility Models for Analysing Stock Returns in Ghana

    Edward Akurugu, Irene Dekomwine Angbing et al.•ARTICLE•Statistics Politics and Policy•2022•References: 1

    The goal of this research was to use Bayesian switching volatility models to model the stock returns of the GCB, bank in Ghana. Monthly stock prices of GCB bank for the period of 138 months were used for the study. The two-state Markov-Switching GARCH models were used in the study to determine the best model for modelling and forecasting the stock returns. The Deviance Information Criteria was considered when selecting the best model. Based on th…

  • Tweedie Regression Analysis of Determinants of Birth Weight in Navrongo

    Emmanuel N-yambi Tegee, Edward Akurugu et al.•ARTICLE•Statistics Politics and Policy•2022•References: 1

    The study modelled and investigated the determinants of infant birth weight by considering maternal and infant factors as predictors. Monthly data spanning for a period of 37 months were obtained from the Navrongo Health Research Centre of the Navrongo Municipality of the Upper East region of Ghana. In modelling the birth weight of infants, the Tweedie regression model and its counterparts of exponential families (Gaussian, Gamma and inverse Gaus…

  • Modelling Factors Affecting Internally Generated Funds of the Tamale Metropolitan Assembly of Ghana Using Multivariate Analysis Techniques

    Saaka Takora, Edward Akurugu et al.•ARTICLE•Statistics Politics and Policy•2023

    The study was carried out to model factors that affect the Internally Generated Funds of the Tamale Metropolitan Assembly using Factor and Confirmatory Factor analysis. The study involved 403 categories of respondents using probability and non-probability sampling techniques. The results from the Factor analysis confirmed a four-factor structure model to accurately represent the observed data without substantial loss of information. The Factor an…

Mathematics (3 works) · Statistics (3 works) · Econometrics (2 works) · Economics (2 works) · Geography (2 works) · Advanced Statistical Methods and Models (1 work) · Akaike information criterion (1 work) · Autoregressive conditional heteroskedasticity (1 work) · Bayesian inference (1 work) · Bayesian probability (1 work)

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