找回密码
 注册
查看: 344|回复: 0

R语言 VGAM包 bisa()函数中文帮助文档(中英文对照)

[复制链接]
发表于 2012-10-1 15:27:22 | 显示全部楼层 |阅读模式
bisa(VGAM)
bisa()所属R语言包:VGAM

                                         Birnbaum-Saunders Distribution Family Function
                                         伯恩鲍姆 - 桑德斯分配家庭功能

                                         译者:生物统计家园网 机器人LoveR

描述----------Description----------

Estimates the shape and scale parameters of the Birnbaum-Saunders distribution by maximum likelihood estimation.
估计伯恩鲍姆Saunders分布参数的最大似然估计的形状和规模。


用法----------Usage----------


bisa(lshape = "loge", lscale = "loge",
     eshape = list(), escale = list(),
     ishape = NULL, iscale = 1, imethod = 1, zero = NULL)



参数----------Arguments----------

参数:lscale, lshape
Parameter link functions applied to the shape and scale parameters (a and b below). See Links for more choices. A log link is the default for both because they are positive.  
参数链接功能,适用于形状和尺度参数(a和b以下)。见Links更多的选择。的log链接都是默认的,因为他们是积极的。


参数:escale, eshape
List. Extra argument for each of the links. See earg in Links for general information.  
列表。每个环节的额外参数。见earg中Links的一般信息。


参数:iscale, ishape
Initial values for a and b. A NULL means an initial value is chosen internally using imethod.  
初始值a和b。 ANULL是指内部选择使用imethod的初始值。


参数:imethod
An integer with value 1 or 2 or 3 which specifies the initialization method. If failure to converge occurs try the other value, or else specify a value for  ishape and/or iscale.   
一个整数,值1或2或3指定的初始化方法。如果收敛失败发生的其他值,否则指定的值ishape和/或iscale。


参数:zero
An integer-valued vector specifying which linear/additive predictors are modelled as intercepts only. The default is none of them. If used, choose one value from the set {1,2}.  
指定一个整数值向量线性/添加剂的预测模型仅作为拦截。在默认情况下是没有。如果使用,选择一个值的集合{1,2}。


Details

详细信息----------Details----------

The (two-parameter) Birnbaum-Saunders distribution  has a cumulative distribution function that can be written as
(两个参数)的伯恩鲍姆-Saunders分布有累积分布函数,该函数可写为

where pnorm() is the  cumulative distribution function of a standard normal (see pnorm), xi(t) = t^(0.5) - t^(-0.5), y > 0, a>0 is the shape parameter, b>0 is the scale parameter. The mean of Y (which is the fitted value) is b*(1 + a*a/2). and the variance is a^2 b^2 (1 + (5/4)*a^2). By default, eta1 = log(a) and eta2 = log(b) for this family function.
pnorm()是标准正态累积分布函数(见pnorm)xi(t) = t^(0.5) - t^(-0.5),y > 0,a>0的形状参数,b>0是尺度参数。的平均值Y(这是拟合值)是b*(1 + a*a/2)。的的方差是a^2 b^2 (1 + (5/4)*a^2)。默认情况下,eta1 = log(a)和eta2 = log(b)家庭功能。

Note that a and b are orthogonal, i.e., the Fisher information matrix is diagonal. This family function implements Fisher scoring, and it is unnecessary to compute any integrals numerically.
需要注意的是a和b是正交的,即Fisher信息矩阵是对角。这的家庭功能实现费舍尔得分,这是不必要的数值计算任何积分。


值----------Value----------

An object of class "vglmff" (see vglmff-class). The object is used by modelling functions such as vglm, and vgam.
类的一个对象"vglmff"(见vglmff-class)。该对象被用于建模功能,如vglm,vgam。


(作者)----------Author(s)----------


T. W. Yee



参考文献----------References----------

Improved statistical inference for the two-parameter Birnbaum-Saunders distribution. Computational Statistics \& Data Analysis, 51, 4656–4681.
A new family of life distributions. Journal of Applied Probability, 6, 319–327.
Estimation for a family of life distributions with applications to fatigue. Journal of Applied Probability, 6, 328–347.
Inferences on the parameters of the Birnbaum-Saunders fatigue life distribution based on maximum likelihood estimation. Technometrics, 23, 251–256.
Continuous Univariate Distributions, 2nd edition, Volume 2, New York: Wiley.

参见----------See Also----------

pbisa, inv.gaussianff.
pbisa,inv.gaussianff。


实例----------Examples----------


bdat1 <- data.frame(x2 = runif(nn <- 1000))
bdat1 <- transform(bdat1, shape = exp(-0.5 + x2), scale = exp(1.5))
bdat1 <- transform(bdat1, y = rbisa(nn, shape, scale))
fit1 <- vglm(y ~ x2, bisa(zero = 2), bdat1, trace = TRUE)
coef(fit1, matrix = TRUE)

## Not run: [#不运行:]
bdat2 <- data.frame(shape = exp(-0.5), scale = exp(0.5))
bdat2 <- transform(bdat2, y = rbisa(nn, shape, scale))
fit <- vglm(y ~ 1, bisa, bdat2, trace = TRUE)
with(bdat2, hist(y, prob = TRUE, ylim = c(0, 0.5), col = "lightblue"))
coef(fit, matrix = TRUE)
with(bdat2, mean(y))
head(fitted(fit))
x <- with(bdat2, seq(0, max(y), len = 200))
lines(dbisa(x, Coef(fit)[1], Coef(fit)[2]) ~ x, bdat2, col = "orange", lwd = 2)
## End(Not run)[#(不执行)]

转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。


注:
注1:为了方便大家学习,本文档为生物统计家园网机器人LoveR翻译而成,仅供个人R语言学习参考使用,生物统计家园保留版权。
注2:由于是机器人自动翻译,难免有不准确之处,使用时仔细对照中、英文内容进行反复理解,可以帮助R语言的学习。
注3:如遇到不准确之处,请在本贴的后面进行回帖,我们会逐渐进行修订。
回复

使用道具 举报

您需要登录后才可以回帖 登录 | 注册

本版积分规则

手机版|小黑屋|生物统计家园 网站价格

GMT+8, 2024-11-26 22:43 , Processed in 0.041549 second(s), 15 queries .

Powered by Discuz! X3.5

© 2001-2024 Discuz! Team.

快速回复 返回顶部 返回列表