Preprint Article Version 1 NOT YET PEER-REVIEWED

Propositions for Confidence Interval in Systematic Sampling on Real Line

  1. Department of Statistics, Faculty of Arts and Science, University of Uşak, Ankara-İzmir Karayolu 8.Km.1.Eylül Kampüsü UŞAK - 64200, Turkey
Version 1 : Received: 2 August 2016 / Approved: 2 August 2016 / Online: 2 August 2016 (11:07:53 CEST)
Version 2 : Received: 16 August 2016 / Approved: 16 August 2016 / Online: 16 August 2016 (11:39:57 CEST)
Version 3 : Received: 9 September 2016 / Approved: 9 September 2016 / Online: 9 September 2016 (11:52:36 CEST)
Version 4 : Received: 14 September 2016 / Approved: 15 September 2016 / Online: 15 September 2016 (05:18:42 CEST)

How to cite: Çankaya, M. Propositions for Confidence Interval in Systematic Sampling on Real Line. Preprints 2016, 2016080017 (doi: 10.20944/preprints201608.0017.v1). Çankaya, M. Propositions for Confidence Interval in Systematic Sampling on Real Line. Preprints 2016, 2016080017 (doi: 10.20944/preprints201608.0017.v1).

Abstract

Systematic sampling on real line (R) when using the different probes is very attractive method within which the biomedical imaging is consulted by a surgery, etc. This study is an extension of [16], and
an exact calculation method is proposed for the calculation of constant λq of confidence interval for the systematic sampling. If the smoothness constant q of measurement function occurred by slicing the three dimensional object is estimated to be enough small mean square error, we can make the important remarks for the design-based stereology used as a method to get the quantitative results from the tissues and the radiological images. Synthetic data can support the results of real data. The currently used covariogram model proposed by [28] is tested for the different measurement functions to see the performance on the variance estimation. The exact value of constant λq is examined for the different measurement functions as well.

Subject Areas

biomedical imaging; covariogram; design-based stereology; estimation of volume; systematic sampling

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