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Exact Distribution of Difference of Two Sample Proportions and Its Inferences 被引量:1
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作者 Keshab R. Dahal Mohamed Amezziane 《Open Journal of Statistics》 2020年第3期363-374,共12页
Comparing two population proportions using confidence interval could be misleading in many cases, such </span><span style="font-family:Verdana;">as</span><span style="font-family:Ve... Comparing two population proportions using confidence interval could be misleading in many cases, such </span><span style="font-family:Verdana;">as</span><span style="font-family:Verdana;"> the sample size </span><span style="font-family:Verdana;">being</span><span style="font-family:Verdana;"> small and the test </span><span style="font-family:Verdana;">being</span><span style="font-family:Verdana;"> based on normal approximation. In this case, the only </span><span style="font-family:Verdana;">one</span><span style="font-family:Verdana;"> option that we have is to collect a large sample. Unfortunately, the large sample might not be possible. One example is a person suffering from a rare disease. The main purpose of this journal is to derive a closed formula for the exact distribution of the difference between two independent sample proportions, and use it to perform related inferences such as a confidence interval, regardless of the sample sizes and compare with the existing Wald, Agresti-Caffo </span><span style="font-family:Verdana;">and</span><span style="font-family:Verdana;"> Score. In this journal, we have derived a closed formula for the exact distribution of the difference between two independent sample proportions. This distribution doesn’t need any </span><span style="font-family:Verdana;">requirements,</span><span style="font-family:Verdana;"> and can be used to perform inferences such </span><span style="font-family:Verdana;">as:</span><span style="font-family:Verdana;"> a hypothesis test for two population proportions, regardless of the nature of the distribution and the sample sizes. We claim </span><span style="font-family:Verdana;">that</span><span style="font-family:Verdana;"> exact distribution has the </span><span style="font-family:Verdana;">least</span><span style="font-family:Verdana;"> confidence width among Wald, Agresti-Caffo </span><span style="font-family:Verdana;">and</span><span style="font-family:Verdana;"> Score, so it is suitable for inferences of the difference between the population proportion regardless of sample size. 展开更多
关键词 Statistical Inferences Exact Distribution Difference of Sample proportions
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Design and research of an LED driving circuit with accurate proportional current sampling mode 被引量:2
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作者 郭维 杨幸 朱大中 《Journal of Semiconductors》 EI CAS CSCD 北大核心 2010年第4期94-98,共5页
An LED driving circuit in accurate proportional current sampling mode is designed and fabricated based on CSMC 0.5 μm standard CMOS technology. It realizes accurate sensing of sampling current variation with output d... An LED driving circuit in accurate proportional current sampling mode is designed and fabricated based on CSMC 0.5 μm standard CMOS technology. It realizes accurate sensing of sampling current variation with output driving current. A better constant output current characteristic is achieved by using an amplifier to clamp the drain voltage of both the sampling MOSFET and power MOSFET to the same value with feedback control. Small signal equivalent circuit analysis shows that the small signal output resistance in the accurate proportional current sampling mode circuit is much larger than that in a traditional proportional current sampling mode circuit, and circuit stability could be assured. Circuit simulation and chip testing results show that when the LED driving current is 350 mA and the power supply is 6 V with ± 10% variation, the stability of the output constant current of the accurate proportional current sampling mode LED driving IC will show 41% improvement over that of a traditional proportional current sampling mode LED driving IC. 展开更多
关键词 LED driver accurate proportional current sampling constant current
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