Jackknife Algorithm on Linear Regression Estimation
DOI:
https://doi.org/10.53555/ms.v1i1.910Keywords:
Jackknife algorithm, simple regression, Pseudo-Values, Confidence interval, Bias, correlation coefficientAbstract
In this paper, interest was on the estimation of simple linear regression data using Jackknife algorithm. Thus, Jackknife delete-one algorithm was employed to provide estimates of simple linear regression coefficient. Observations on systolic blood pressure (SBP) and age for a sample of 30 randomly selected patients were collected from Federal Medical Centre Owerri Imo State Nigeria. It was discovered that all errors in the ydirection are normally distributed. The statistical software known as Stata version 9.1 was employed for the ease of the analysis. Pseudo-Values, Jackknife Estimates, and the Jackknife Standard Error were computed. From the analysis, it was revealed that the bias result of the correlation was positive. The result from the OLS shows that SBP on Age of patients is significant. The jackknife standard error and confidence intervals of the Age coefficient based on the distribution J F ˆ are substantially larger than the estimated OLS standard error due to the inadequacy of the jackknife in small samples. Comparing the jackknife coefficients averages J 0 ˆ and J 1 ˆ with the corresponding OLS estimates 0 ˆ and 1 ˆ shows that there is a little bias in the jackknife coefficients.
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