Application of Bivariate Conditional Rayleigh Distribution in Cardiovascular (Blood Pressure and Heart Rate) Data Examination

The objective of this paper is to apply bivariate conditional Rayleigh distribution in cardiovascular (blood pressure and heart rate) data examination, where the conditional dependence of the two variables is suspected. The goodness–of–fit of the model was tested using various standard methods, result revealed model adequacy for blood pressure given heart rate and heart rate given blood pressure. This suggests that the proposed model is compatible with the data and efficient. Thus, the proposed model is recommended when there is a need to account for a conditional structure characterized by underlining uncertainties in a bivariate variable.

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Publication Details

Journal
Journal of applied science and environmental management
Published
2025-06-02
DOI
https://doi.org/10.4314/jasem.v29i5.14
Primary Topic
Non-Invasive Vital Sign Monitoring
Type
article
Field-Weighted Citation Impact
0.00
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article

Application of Bivariate Conditional Rayleigh Distribution in Cardiovascular (Blood Pressure and Heart Rate) Data Examination

O.P. Otaru, N. P. Ogbonda
Journal of applied science and environmental management
Non-Invasive Vital Sign Monitoring
article

Application of Bivariate Conditional Rayleigh Distribution in Cardiovascular (Blood Pressure and Heart Rate) Data Examination

O.P. Otaru, N. P. Ogbonda
article en

Abstract

The objective of this paper is to apply bivariate conditional Rayleigh distribution in cardiovascular (blood pressure and heart rate) data examination, where the conditional dependence of the two variables is suspected. The goodness–of–fit of the model was tested using various standard methods, result revealed model adequacy for blood pressure given heart rate and heart rate given blood pressure. This suggests that the proposed model is compatible with the data and efficient. Thus, the proposed model is recommended when there is a need to account for a conditional structure characterized by underlining uncertainties in a bivariate variable.

Journal of applied science and environmental managementVol. 29(5)
Openalex Percentile: Top 85%
Non-Invasive Vital Sign Monitoring
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