An exploratory investigation on the application of the bootstrapping technique to the jackknife estimates of the truncation point of continuous distributions

This thesis presents an application of the bootstrapping technique to jackknife estimates of the truncation point of continuous distributions. All of the estimators used in this study are presented by Ma. Vanessa Santos and Edwin Tajanlangit in their thesis entitled, An Exposition on the Viability of the Jackknife Statistics in the Estimation of the Truncation point of Continuous Distributions. These estimators are the jackknife estimator, the first, second, and third order generalized jackknife estimators, symbolized as J(8), G1(8), G2(8), and G3(8), respectively. The estimators established using the jackknife procedure are applied to the truncated exponential distribution using Monte Carlo simulations to estimate the specified truncation point. Computed values of the generalized jackknife are taken randomly to make another estimate of the truncation point. This constituted the bootstrap part of the data simulation. Different sample sizes and replications are used. Results show that the application of bootstrap to the jackknife estimates, the estimators, particularly the maximum likelihood estimator (MLE) produce estimates which are much closer in value to the point of truncation