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Median and Extreme Ranked Set Sampling for penalized spline estimation |
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PP: 243-250 |
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doi:10.18576/amis/100124
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Author(s) |
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Ali Algarni,
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Abstract |
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| This paper improves and demonstrates two approaches of Ranked Set Sampling (RSS) method for penalized spline models
which are Median and Extreme RSS. These improved methods increase the efficiency of the estimated parameters in the targeted model
with comparing to usual RSS and Simple Random Sampling (SRS). Moreover, in practical studies, our improved methods can reduce
sampling expenses dramatically. The paper approaches are illustrated using a simulation study as well as a practical example. |
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