Fitting polynomial trend to time series by the method of Buys-Ballot estimators

Nduka, Uchenna Chinedu; Iwueze, S. I.; Nwogu, Eleazar C.

doi:10.1080/03610926.2015.1085569

Cited by 4 publications

(5 citation statements)

References 7 publications

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“…For the purpose of data collection and analysis, primary data was collected through questionnaires which were administered to the staff of different hospitals which have either adopted the electronic healthcare style of hospital management or the manual method of keeping patient information. One hundred and fifty respondents were selected on the basis of simple random sampling (Nduka, 2015) from selected hospitals in Yenagoa of Bayelsa State of Nigeria in West Africa. The division of the data collection was made on the basis of 75 respondents from hospitals which have adopted the electronic healthcare style (EHS) and 75 respondents from hospitals using the manual method of keeping patient records.…”

Section: Data Collection and Analysismentioning

confidence: 99%

“…The data will be extracted from the questionnaires and the necessary information will be compiled using R Statistical Software (R Development Core Team). The data collected will be analyzed using some statistical tools such as the measures of central tendency and Chi square test (Nduka, 2015) to find out the inferences of the research. The demographic data of the respondents by professions, sex and age are presented in Table 2.…”

Section: Data Collection and Analysismentioning

confidence: 99%

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Performance Evaluation of Adopting the Electronic Style in Hospital Services

Consul

Japheth

Erho

2021

International Journal of Applied Research on Public Health Management

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Globally, health information systems and technologies are being used increasingly and are seen as a way to increase the efficiency and quality of patient care. One of the factors blocking the use of electronic healthcare system from widespread acceptance as experienced in the manual method is the concern about patients' data confidentiality. This paper is set to discuss and appraise the adoption of electronic style in the provision and management of hospital services for efficiency, accuracy, and timely delivery of services in order to enhance the data confidentiality. Data collected from questionnaire were analysed and evaluated based on two identified significant aspects: the problems of either adopting the electronic healthcare or manual system of keeping patient information and the efficiency, problems, and barriers of adopting the electronic healthcare style in hospitals. It is observed that the adoption of electronic style will improve interactivity in all areas of specialization in hospital management.

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Section: Data Collection and Analysismentioning

confidence: 99%

Section: Data Collection and Analysismentioning

confidence: 99%

Performance Evaluation of Adopting the Electronic Style in Hospital Services

Consul

Japheth

Erho

2021

International Journal of Applied Research on Public Health Management

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“…The high level of multicollinearity between two or more powers of the time variable(t) in a polynomial trend model often results in wrong inferences and model selection based on the least squares estimates of the concerned parameters [4,24]. As a consequence, the Buys-Ballot estimation procedure proposed in [12], which is capable of yielding estimates that are robust to multicollinearity, is considered when the multicollinearity problem exists [21]. The Buys-Ballot approach is primarily used for the decomposition of a relatively short series such that the trend and cyclical components are jointly estimated.…”

Section: Introductionmentioning

confidence: 99%

Buys-Ballot Technique for the Analysis of Time Series with a Cubic-Trend Component

Okereke

Omekara

Ekezie

2018

J Indian Soc Probab Stat

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Time series, especially those with the cubic trend component, are encountered in many data analysis situations. The decomposition of such series into various components requires a method that can adequately estimate the cubic trend as well as other components of the series. In this study, the chain base, fixed base and classical methods of decomposition of time series with the cubic trend component are discussed with emphasis on the additive model. Chain base and fixed base estimators of the additive model parameters are derived. Basic properties of these two classes of estimators are equally determined. The derived chain base variables have the autocorrelation structure of an invertible third-order moving average model. The chain base estimators are found to be pairwise-negatively correlated estimators. Though the classical method and chain base method are both used for time series decomposition, the chain base method is recommended when a case of multicollinearity has been established.

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“…The high level of multicollinearity between two or more powers of the time variable(t) in a polynomial trend model often results in wrong inferences and model selection based on the least squares estimates of the concerned parameters [4,24]. As a consequence, the Buys-Ballot estimation procedure proposed in [12], which is capable of yielding estimates that are robust to multicollinearity, is considered when the multicollinearity problem exists [21]. The Buys-Ballot approach is primarily used for the decomposition 249 of a relatively short series such that the trend and cyclical components are jointly estimated.…”

Section: Introductionmentioning

confidence: 99%

“…These authors equally found the best linear unbiased estimate of the slope parameter using the variables associated with the chain base estimation. Works carried out in other areas of research interest in the Buys-Ballot Method include the development of the procedures through which one can determine when each of the additive and multiplicative models should be considered [14], test for the presence of seasonal variations [22] and the influence of the mis-specification of error distribution on the prediction accuracy of the fitted Buy-Ballot model [21].…”

Section: Introductionmentioning

confidence: 99%