In this paper, we consider the construction of the approximate profile-</span><span style="font-family:""> </span><span style="font-family:Verdana;">likelihood confiden...In this paper, we consider the construction of the approximate profile-</span><span style="font-family:""> </span><span style="font-family:Verdana;">likelihood confidence intervals for parameters of the 2-parameter Weibull distribution based on small type-2 censored samples. In previous research works, the traditional Wald method has been used to construct approximate confidence intervals for the 2-parameter Weibull distribution</span><span style="font-family:""> </span><span style="font-family:Verdana;">under type-2 censoring scheme. However, the Wald technique is based on normality assumption and thus may not produce accurate interval estimates for small samples. The profile-likelihood and Wald confidence intervals are constructed for the shape and scale parameters of the 2-parameter Weibull distribution based on simulated and real type-2 censored data, and are hence compared using confidence length and coverage probability.展开更多
This paper presents four methods of constructing the confidence interval for the proportion <i><span style="font-family:Verdana;">p</span></i><span style="font-family:;" ...This paper presents four methods of constructing the confidence interval for the proportion <i><span style="font-family:Verdana;">p</span></i><span style="font-family:;" "=""><span style="font-family:Verdana;"> of the binomial distribution. Evidence in the literature indicates the standard Wald confidence interval for the binomial proportion is inaccurate, especially for extreme values of </span><i><span style="font-family:Verdana;">p</span></i><span style="font-family:Verdana;">. Even for moderately large sample sizes, the coverage probabilities of the Wald confidence interval prove to be erratic for extreme values of </span><i><span style="font-family:Verdana;">p</span></i><span style="font-family:Verdana;">. Three alternative confidence intervals, namely, Wilson confidence interval, Clopper-Pearson interval, and likelihood interval</span></span><span style="font-family:Verdana;">,</span><span style="font-family:Verdana;"> are compared to the Wald confidence interval on the basis of coverage probability and expected length by means of simulation.</span>展开更多
文摘In this paper, we consider the construction of the approximate profile-</span><span style="font-family:""> </span><span style="font-family:Verdana;">likelihood confidence intervals for parameters of the 2-parameter Weibull distribution based on small type-2 censored samples. In previous research works, the traditional Wald method has been used to construct approximate confidence intervals for the 2-parameter Weibull distribution</span><span style="font-family:""> </span><span style="font-family:Verdana;">under type-2 censoring scheme. However, the Wald technique is based on normality assumption and thus may not produce accurate interval estimates for small samples. The profile-likelihood and Wald confidence intervals are constructed for the shape and scale parameters of the 2-parameter Weibull distribution based on simulated and real type-2 censored data, and are hence compared using confidence length and coverage probability.
文摘This paper presents four methods of constructing the confidence interval for the proportion <i><span style="font-family:Verdana;">p</span></i><span style="font-family:;" "=""><span style="font-family:Verdana;"> of the binomial distribution. Evidence in the literature indicates the standard Wald confidence interval for the binomial proportion is inaccurate, especially for extreme values of </span><i><span style="font-family:Verdana;">p</span></i><span style="font-family:Verdana;">. Even for moderately large sample sizes, the coverage probabilities of the Wald confidence interval prove to be erratic for extreme values of </span><i><span style="font-family:Verdana;">p</span></i><span style="font-family:Verdana;">. Three alternative confidence intervals, namely, Wilson confidence interval, Clopper-Pearson interval, and likelihood interval</span></span><span style="font-family:Verdana;">,</span><span style="font-family:Verdana;"> are compared to the Wald confidence interval on the basis of coverage probability and expected length by means of simulation.</span>
