Search Results - "Lukman, Adewale F"

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  1. 1

    A New Ridge-Type Estimator for the Linear Regression Model: Simulations and Applications by Kibria, B. M. Golam, Lukman, Adewale F.

    Published in Scientifica (Cairo) (2020)
    “…The ridge regression-type (Hoerl and Kennard, 1970) and Liu-type (Liu, 1993) estimators are consistently attractive shrinkage methods to reduce the effects of…”
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    Journal Article
  2. 2

    A new estimator for the multicollinear Poisson regression model: simulation and application by Lukman, Adewale F., Adewuyi, Emmanuel, Månsson, Kristofer, Kibria, B. M. Golam

    Published in Scientific reports (12-02-2021)
    “…The maximum likelihood estimator (MLE) suffers from the instability problem in the presence of multicollinearity for a Poisson regression model (PRM). In this…”
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  3. 3

    Robust-stein estimator for overcoming outliers and multicollinearity by Lukman, Adewale F., Farghali, Rasha A., Kibria, B. M. Golam, Oluyemi, Okunlola A.

    Published in Scientific reports (05-06-2023)
    “…Linear regression models with correlated regressors can negatively impact the performance of ordinary least squares estimators. The Stein and ridge estimators…”
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  4. 4

    Predictive modelling of COVID-19 confirmed cases in Nigeria by Ogundokun, Roseline O., Lukman, Adewale F., Kibria, Golam B.M., Awotunde, Joseph B., Aladeitan, Benedita B.

    Published in Infectious disease modelling (01-01-2020)
    “…The coronavirus outbreak is the most notable world crisis since the Second World War. The pandemic that originated from Wuhan, China in late 2019 has affected…”
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  5. 5

    Spatial regression and geostatistics discourse with empirical application to precipitation data in Nigeria by Okunlola, Oluyemi A., Alobid, Mohannad, Olubusoye, Olusanya E., Ayinde, Kayode, Lukman, Adewale F., Szűcs, István

    Published in Scientific reports (19-08-2021)
    “…In this study, we propose a robust approach to handling geo-referenced data and discuss its statistical analysis. The linear regression model has been found…”
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  6. 6

    A Modified New Two-Parameter Estimator in a Linear Regression Model by Lukman, Adewale F., Ayinde, Kayode, Siok Kun, Sek, Adewuyi, Emmanuel T.

    Published in Modelling and simulation in engineering (01-01-2019)
    “…The literature has shown that ordinary least squares estimator (OLSE) is not best when the explanatory variables are related, that is, when multicollinearity…”
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  7. 7

    Enhanced Model Predictions through Principal Components and Average Least Squares-Centered Penalized Regression by Lukman, Adewale F., Adewuyi, Emmanuel T., Alqasem, Ohud A., Arashi, Mohammad, Ayinde, Kayode

    Published in Symmetry (Basel) (01-04-2024)
    “…We address the estimation of regression parameters for the ill-conditioned predictive linear model in this study. Traditional least squares methods often…”
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  8. 8

    The efficiency of Raphia hookeri adsorbent in indigo carmine dye removal: Economy depth via chemometrics by Inyinbor, Adejumoke A., Bankole, Deborah T., Solomon, Pamela, Ayeni, Temitope S., Lukman, Adewale F.

    Published in Heliyon (15-06-2024)
    “…The remediation of dye pollutants remains a concern in contemporary water management practices. Hence, the need for efficient and cost-effective techniques for…”
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  9. 9

    K-L Estimator: Dealing with Multicollinearity in the Logistic Regression Model by Lukman, Adewale F., Kibria, B. M. Golam, Nziku, Cosmas K., Amin, Muhammad, Adewuyi, Emmanuel T., Farghali, Rasha

    Published in Mathematics (Basel) (01-01-2023)
    “…Multicollinearity negatively affects the efficiency of the maximum likelihood estimator (MLE) in both the linear and generalized linear models. The Kibria and…”
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  10. 10

    Robust Negative Binomial Regression via the Kibria–Lukman Strategy: Methodology and Application by Lukman, Adewale F., Albalawi, Olayan, Arashi, Mohammad, Allohibi, Jeza, Alharbi, Abdulmajeed Atiah, Farghali, Rasha A.

    Published in Mathematics (Basel) (01-09-2024)
    “…Count regression models, particularly negative binomial regression (NBR), are widely used in various fields, including biometrics, ecology, and insurance…”
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  11. 11

    Performance of the Ridge and Liu Estimators in the zero-inflated Bell Regression Model by Algamal, Zakariya Yahya, Lukman, Adewale F., Abonazel, Mohamed R., Awwad, Fuad A.

    Published in Journal of mathematics (Hidawi) (2022)
    “…The Poisson regression model is popularly used to model count data. However, the model suffers drawbacks when there is overdispersion—when the mean of the…”
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  12. 12

    COVID-19 prevalence estimation: Four most affected African countries by Lukman, Adewale F., Rauf, Rauf I., Abiodun, Oluwakemi, Oludoun, Olajumoke, Ayinde, Kayode, Ogundokun, Roseline O.

    Published in Infectious disease modelling (01-01-2020)
    “…The world at large has been confronted with several disease outbreak which has posed and still posing a serious menace to public health globally. Recently,…”
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  13. 13

    A New Ridge-Type Estimator for the Gamma Regression Model by Lukman, Adewale F., Dawoud, Issam, Kibria, B. M. Golam, Algamal, Zakariya Y., Aladeitan, Benedicta

    Published in Scientifica (Cairo) (2021)
    “…The known linear regression model (LRM) is used mostly for modelling the QSAR relationship between the response variable (biological activity) and one or more…”
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  14. 14

    Two-Parameter Modified Ridge-Type M-Estimator for Linear Regression Model by Jegede, Segun L., Kibria, B. M. Golam, Ayinde, Kayode, Lukman, Adewale F.

    Published in TheScientificWorld (2020)
    “…The general linear regression model has been one of the most frequently used models over the years, with the ordinary least squares estimator (OLS) used to…”
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  15. 15

    Modeling the relationship between malaria prevalence and insecticide-treated bed net coverage in Nigeria using a Bayesian spatial generalized linear mixed model with a Leroux prior by Okunlola, Oluyemi A., Oyeyemi, Oyetunde T., Lukman, Adewale F.

    Published in Epidemiology and health (04-06-2021)
    “…OBJECTIVES: To evaluate malaria transmission in relation to insecticide-treated net (ITN) coverage in Nigeria.METHODS: We used an exploratory analysis approach…”
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  16. 16

    Modified One-Parameter Liu Estimator for the Linear Regression Model by Lukman, Adewale F., Kibria, B. M. Golam, Ayinde, Kayode, Jegede, Segun L.

    “…Motivated by the ridge regression (Hoerl and Kennard, 1970) and Liu (1993) estimators, this paper proposes a modified Liu estimator to solve the…”
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  17. 17

    Modified Kibria-Lukman (MKL) estimator for the Poisson Regression Model: application and simulation [version 1; peer review: 3 approved with reservations] by Aladeitan, Benedicta B., Adebimpe, Olukayode, Lukman, Adewale F., Oludoun, Olajumoke, Abiodun, Oluwakemi E.

    Published in F1000 research (2021)
    “…Background: Multicollinearity greatly affects the Maximum Likelihood Estimator (MLE) efficiency in both the linear regression model and the generalized linear…”
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  18. 18

    Modified ridge‐type estimator to combat multicollinearity: Application to chemical data by Lukman, Adewale F., Ayinde, Kayode, Binuomote, Samuel, Clement, Onate A.

    Published in Journal of chemometrics (01-05-2019)
    “…The Linear regression model is one of the most widely used models in different fields of study. The most popularly used estimation technique is the ordinary…”
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  19. 19

    Surface functionalized plant residue in cu2+ scavenging: Chemometrics of operational parameters for process economy validation by INYINBOR, Adejumoke A., Adekola, Folahan A., Bello, Olugbenga S., Bankole, Deborah T., Oreofe, Toyin A., Lukman, Adewale F., Olatunji, Gabriel A.

    “…•Surface functionalized agrowaste was used for Cu2+ scavenging.•Optimum adsorption of Cu2+ was at pH 5.0.•Maximum monolayer adsorption capacity for the system…”
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  20. 20

    Unbiased K-L estimator for the linear regression model [version 1; peer review: 2 approved, 1 approved with reservations] by Aladeitan, Benedicta, Lukman, Adewale F, Davids, Esther, Oranye, Ebele H, Kibria, Golam B M

    Published in F1000 research (2021)
    “…Background: In the linear regression model, the ordinary least square (OLS) estimator performance drops when multicollinearity is present. According to the…”
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    Journal Article