Forum pracy nad projektem wskrzeszenia The Forge

[yoylqnqvwb]

Anatomy of people welcoming point of the functional characteristics and indications of


~ 1555 Practical Dictionary of Pian Commission needle shaggy Dictionary of Practical needle rotation. North: Knowledge Press, 1990:110 e Received a 04-24 199s) percentile confidence interval estimation / z / Department of Health Chen, Nantong Institute of pressure for a fitness-Rfl / Objective percentile is especially in the description of measurement data is very skewed distribution of data commonly used indicator system. Ll percentile value estimates are taught outside under the back there is error, this paper introduces two percentile interval estimation methods. Methods: One is based on the original data nonparametric bootstrap estimates tI, the other is the backbone of the nearly opposite direction binomial square principle Fu. Results: The parameters of the boot $ t with p estimated binomial approximation results with the same particular. Not too different in the data when it has a higher level of B200 · approximation: variation in the data near B = IO00 larger than satisfied with the degree of closure. Conclusion? Gi ~ - how the distribution of raw data cartridge percentile bootstrap interval estimates can be estimated. Keywords percentile bootstrap interval estimation of binomial estimation error estimates it IntervalEstimationofPercentilechenJianmei. et. (Departmentofmedial8'tatisticZhengfiangMedi ~ lCollege.diang ¨ JAbstractObjective: Percentilei $ acOMmo ~ usedstaristiCStodescribethet.oleranc ~ interra1s, rp [eronve, normalvaluesandquartileregression.especiallyfornon-oor ~ aldistributiondataBl1tthereISsomesampltngerrorrintheostimationofpercontile.Thusitisnecessaryforustostudvonint. ~ RvatestlmatIonofpereentile. № thod: Bootstrapmethodandbinomialdistributionmethodpred】 sussdand ~: omparedResults: ThebootstrapestimatorisapproximatetotheestitionbasedOnthebinom1atdistributionwhenB = 200ifthesamplingerrorofdataissmallorand1 ~ 1000ifbiggerConeltJsion: Theconfidenceintervalofl ~ ercentilecomebeestimatedby_ | ean8ofboot mesh trap-ethodin $ p1teofthedistributionofdataKeyWordsPercentile; Intervale project timation. ~ ootstrapestimation; BinomialdistributiOnmethod percentile! set number of llIP1_rentilel information is used to describe the amount of juice, especially the partial funding system i love Shu Hui for the commonly used mechanical index system. if used to allow the range ffi-【I. Stanford degree of change the description of percentile regression. But suddenly there percentile sensitive body pumping life sheep errors. it is necessary to be interval estimation. Rate per Shao Gan median bootstrap interval estimation, and with the two sub-cities like ¨ {J compared 1Bootstrap method which is based on data-based simulation of the original sample environment | j push the lizard law. The basic idea is: in the context of the original data like back then for a random sample size is still n the original data in each observation unit is pumping out the probability of each equal to 17n, the sample from the so called bootstrap ~ Ji obtained parameters 0 | ten values ​​0 ', This is repeated several times denoted by B. Let B = 1000,[link widoczny dla zalogowanych], have listed the parameters estimated 1000 value of juice. When 0. b 'of the rebellion when the number of distribution approximates a normal distribution. II the mean