Estimating sample mean under interval uncertainty and constraint on sample variance
نویسندگان
چکیده
منابع مشابه
Estimating Mean and Variance under Interval Uncertainty: Dynamic Case
In many practical situations, it is important to estimate the mean E and the variance V from the sample values x1, . . . , xn. Usually, in statistics, we consider the case when the parameters like E and V do not change with time and when the sample values xi are known exactly. In practice, the values xi come from measurements, and measurements are never 100% accurate. In many cases, we only kno...
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In sample surveys, we always deal with two types of errors: Sampling error and non-sampling error. One of the most common non-sampling errors is nonresponse. This error happens when some sample units are not observed or viewed but they do not answer some of the questions. The complete prevention of this error is not possible, but it can be significantly reduced. The non-response causes bias and ...
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The problem of the sample variance computation for epistemic inter-val-valued data is, in general, NP-hard. Therefore, known efficient algorithms for computing variance require strong restrictions on admissible intervals like the no-subset property or heavy limitations on the number of possible intersections between intervals. A new asymptotic algorithm for computing the upper bound of the samp...
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Once we have a collection of values corresponding a class of objects, a usual way to decide whether a new object with the value of the corresponding property belongs to this class is to check whether this value belongs to interval from mean E minus k sigma σ to mean plus k sigma, where the parameter k is determined by the degree of confidence with which we want to make the decision. For each va...
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ژورنال
عنوان ژورنال: International Journal of Approximate Reasoning
سال: 2011
ISSN: 0888-613X
DOI: 10.1016/j.ijar.2011.06.002