Inference About the First-Order Autoregressive Coefficient

Provost, Serge B.; Sanjel, Deepak

doi:10.1081/sta-200056847

Cited by 5 publications

(1 citation statement)

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“…2. Using similar approach, Provost and Sanjel (2005) recently discussed inference for various estimators of the first order autoregressive parameter.…”

Section: Density Approximants In Terms Of Orthogonal Polynomialsmentioning

confidence: 96%

Use of Orthogonal Polynomial Approximations for Inference in Exponential Distribution Based on K-Sample Doubly Type-II Censored Data

Sanjel

2006

Communications in Statistics - Theory and Methods

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Hermite and Laguerre polynomial density approximants have been utilized in order to make inference for the location and scale parameters of an exponential distribution based on K-sample Type-II censored data. First, we evaluate the exact moments of the pivots based on the Best Linear Unbiased Estimators (BLUEs) of the parameters and then, based on these moments, their density approximations are obtained using orthogonal polynomials. A comparative study of the percentiles obtained from the orthogonal polynomial approximation of the distributions of the pivots and the resulting interval estimation of the parameters to the corresponding exact numerical results of Balakrishnan and Lin (2005) and Balakrishnan et al. (2004) is carried out. A comparison is also made with the approximate inference based on the maximum likelihood estimators (MLEs) of the parameters. These comparative studies reveal that the proposed density approximant-based techniques provide very accurate inference.

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“…2. Using similar approach, Provost and Sanjel (2005) recently discussed inference for various estimators of the first order autoregressive parameter.…”

Section: Density Approximants In Terms Of Orthogonal Polynomialsmentioning

confidence: 96%