stdClass Object
(
    [id] => 7816
    [paper_index] => EW201904-01-002769
    [title] => FORMULATION OF CUMULATIVE INTERVALS AS A MEASURE OF RELIABILITY FOR THE ASSESSMENT OF SAMPLE MEAN BEHAVIOUR.
    [description] => <ol>
	<li>Abundo, M. (2002). Some Conditional Crossing Results of Brownian Motion Over a Piecewise-Linear Boundary. <em>Statistics and Probability Letters</em>, <em>58 </em>(2), 131&ndash;145.</li>
	<li>Atkinson, M. P. &amp; Singham, D. I. (2015). Multidimensional Hitting Time Re- sults for Brownian Bridges with Moving a Hyoerolanar Boundaries. <em>Statistics and Probability Letters</em>, <em>100</em>, 85&ndash;92.</li>
	<li>Scheike, T. H. (1992). A Boundry-Crossing Results for Brownian Motion. <em>Journal of Applied Probability</em>, <em>29 </em>(2), 448&ndash;453.</li>
	<li>Schruben, L. (1982). Confidence Interval Estimation Using Time Series. <em>Opera- </em><em>tions Research</em>, <em>36 </em>(6), 1090&ndash;1106.</li>
	<li>Singham, D. I. &amp; Atkinson, M. P. (2014). Estimating Cumulative Mean Behavior Using Standardized Time Series.</li>
	<li>Singham, D. I. &amp; Atkinson, M. P. (2015). Construction of Cumulative Mean Bounds for Simulation Output Analysis.</li>
</ol>

    [author] => Peter O. Peter
    [googlescholar] => https://scholar.google.co.in/citations?user=KeqZGcIAAAAJ&hl=en
    [doi] => 
    [year] => 2019
    [month] => April
    [volume] => 7
    [issue] => 4
    [file] => eprapub/EW201904-01-002769.pdf
    [abstract] => <p style="margin-left:34.9pt;">We propose a new measure of reliability, called the cumulative mean intervals, that assesses the mean behaviour of a process by computing the probability that the cumulative sample mean will remain below its long-term sample mean with a given tolerance over a period of time. We further derive a lower bound for the measure when the underlying data is independent and identically distributed with a normal distribution. This deduction provides a preliminary basis for parallel extensions to the two limiting case when we compute the probability that the sample mean stays within a given distance from the true mean with no assumptions made on independence and normality.</p>

<p style="margin-left:34.9pt;"><strong>KEYWORDS: </strong>cumulative mean, probability, reliability, intervals, sample mean.</p>

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    [orderr] => 4
    [journal_id] => 4
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    [edit_on] => 
    [is_status] => 1
    [journalname] => EPRA International Journal of Economic and Business Review(JEBR)
    [short_code] => IJES
    [eissn] => 2347-9671 (O), 2349-0187(P)
    [pissn] => 
    [home_page_wrapper] => images/products_image/12.JEBR.png
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