全部文献期刊学位论文会议报纸专利标准年鉴图书|学者科研项目
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作者:Kayode Ayinde , Sek Siok Kun
来源:[J].Modelling and Simulation in Engineering, 2019, Vol.2019DOAJ
摘要:The literature has shown that ordinary least squares estimator (OLSE) is not best when the explanatory variables are related, that is, when multicollinearity is present. This estimator becomes unstable and gives a misleading conclusion. In this study, a modified new two-parameter...
作者:Tinuke L. Johnson , Kayode Ayinde , Benjamin A. Oyejola
来源:[J].Electronic Journal of Applied Statistical Analysis, 2010, Vol.3 (2), pp.115DOAJ
摘要:In simultaneous equations model, multicollinearity and status of identification of the equations have been observed to influence estimation of the model parameters. The error terms of each equation in the model are also expected to be correlated with each other. This study t...
作者:Kayode Ayinde , Adewale F. Lukman , Olatunji Arowolo
来源:[J].Open Journal of Statistics, 2015, Vol.05 (04), pp.273-283Scientific Research Publishing
摘要:In regression analysis, data sets often contain unusual observations called outliers. Detecting these unusual observations is an important aspect of model building in that they have to be diagnosed so as to ascertain whether they are influential or not. Different influential...
作者:Kayode Ayinde
来源:[J].Journal of Mathematics and Statistics, 2007, Vol.3 (4), pp.196DOAJ
摘要:The Classical Linear Regression Model assumes that regressors are non – stochastic, independent and uncorrelated with the error terms. These assumptions are not always tenable especially where regressors are not often assumed fixed in repeated sampling. In this paper, withst...
作者:O.O. Alabi , Kayode Ayinde , T.O. Olatayo
来源:[J].Journal of Mathematics and Statistics, 2008, Vol.4 (2), pp.75DOAJ
摘要:Inferences on the parameter estimates of Ordinary Least Square (OLS) estimator in regression model when regressors exhibit multicollinearity is a problem in that large standard errors ofthe regression coefficients which cause low t-statistic value often result into the acceptance...
作者:Kayode Ayinde , Sek Siok Kun ...
来源:[J].Modelling and Simulation in Engineering, 2019, Vol.2019Hindawi
摘要:The literature has shown that ordinary least squares estimator (OLSE) is not best when the explanatory variables are related, that is, when multicollinearity is present. This estimator becomes unstable and gives a misleading conclusion. In this study, a modified new two-parameter...
作者:Kayode Ayinde , Emmanuel O. Apata , Oluwayemisi O. Alaba
来源:[J].Open Journal of Statistics, 2012, Vol.02 (05), pp.534-546Scientific Research Publishing
摘要:The development of many estimators of parameters of linear regression model is traceable to non-validity of the assumptions under which the model is formulated, especially when applied to real life situation. This notwithstanding, regression analysis may aim at prediction. C...
作者:Adewale F. Lukman , Kayode Ayinde
来源:[J].Journal of Data Science, 2018, Vol.16 (2), pp.207-217Airiti
摘要:Influential observations do posed a major threat on the performance of regression model. Different influential statistics including Cook's Distance and DFFITS have been introduced in literatures using Ordinary Least Squares (OLS). The efficiency of these measures will be aff...

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