具有参数shape和scale的威布尔分布的密度、分布函数、分位数函数和随机生成。 用法 dweibull(x, shape, scale =1, log =FALSE) pweibull(q, shape, scale =1, lower.tail =TRUE, log.p =FALSE) qweibull(p, shape, scale =1, lower.tail =TRUE, log.p =FALSE) rweibull(n, shape, scale =1) ...
同时,注意到表格下方标签处,出现新的子表格‘Webull1’,如图4的红圈所示。绘制多列图需要基于该表中的数据:A、B列用于绘制原始数据散点;C、D列用于绘制拟合出的直线;E、F则是分布参数,Scale参数表示击穿概率为63.2%时的外施电场强度,Shape参数则表示该样品击穿场强的测试分散程度,越大则测试数据越稳定。 图4 ...
它由三个参数来描述,分别是尺度参数(scale parameter),形状参数(shape parameter)和位置参数(position parameter)。 1. 尺度参数(Scale Parameter):尺度参数表示分布的尺度或者说是分布的缩放因子。它决定了分布的范围和形状。通常用符号β表示。尺度参数越大,分布的范围越宽,尾部越长。 2. 形状参数(Shape Parameter...
利用Weibull分布的参数,计算概率 # survreg's scale = 1/(rweibull shape) # survreg's intercept = log(rweibull scale) ## reponse rweibull shape <- 1/fit1$scale ##weibull分布形状参数 scale <- exp(fit1$coefficients[1]) ##weibull分布尺度参数 p <- 1-pweibull(sort(data$time),shape = sha...
Performs a goodness-of-fit test for Weibull distribution(weibullness test)and provides the pa- rameter estimates of the two-and three-parameter Weibull distributions.Note that the thresh- old parameter is estimated based on the correlation from the Weibull plot.For more de- tails,see<doi:10....
A field method to calculate Weibull distribution shape and scale A field method for calculation of Weibull distribution shape andHaviaras, Gilberto JorgeFrancisco, GilbertoSouza, Martha De
publicWeibullDistribution(doubleshape,doublescale) { if(shape<=0) thrownewArgumentOutOfRangeException( "Shape parameter must be positive"); if(scale<=0) thrownewArgumentOutOfRangeException( "Scale parameter must be positive"); DefineParameters(shape, scale); ...
β为形状参数(shape),η为尺度参数(scale). 且有: β<1,属早期故障型.β>1,属耗损故障型.β=1, 属偶发故障型. 1.2可靠度 可靠度表示在规定的条件下,在规定的时间内 完成规定功能的概率. 式中: t为规定的时间,T为系统的寿命,R(t)为系统
It is sometimes reasonable to assume that the lifetime distribution of an item belongs to a certain parametric family, and that actual parameter values depend upon the testing environment of the item. In the two-parameter Weibull family setting, suppose both the shape and scale parameters are ...
S. M. Homan "A comparison of plotting rules under L1 and L2 estimation of the Weibull scale and shape parameters in situations of small samples with possible censoring and outliers", Commun. Statistics- Simulation & Computation , vol. 18, no. 1, pp.121 -143 1989...