betageometric(VGAM)
betageometric()所属R语言包：VGAM
Beta-geometric Distribution Family Function
β-几何分布的家庭功能
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Maximum likelihood estimation for the beta-geometric distribution.
最大似然估计的β-几何分布。
用法----------Usage----------
betageometric(lprob = "logit", lshape = "loge",
eprob = list(), eshape = list(),
iprob = NULL, ishape = 0.1,
moreSummation=c(2,100), tolerance=1.0e-10, zero=NULL)
参数----------Arguments----------
参数：lprob, lshape
Parameter link functions applied to the parameters prob and phi (called prob and shape below). The former lies in the unit interval and the latter is positive. See Links for more choices.
参数链接功能的参数prob和phi（称为prob和shape以下）。前者在于在单位间隔，后者是正的。见Links更多的选择。
参数：eprob, 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：iprob, ishape
Numeric. Initial values for the two parameters. A NULL means a value is computed internally.
数字。的两个参数的初始值。 ANULL是指在内部计算的值。
参数：moreSummation
Integer, of length 2. When computing the expected information matrix a series summation from 0 to moreSummation[1]*max(y)+moreSummation[2] is made, in which the upper limit is an approximation to infinity. Here, y is the response.
整数，长度为2。当计算预期的信息矩阵从0moreSummation[1]*max(y)+moreSummation[2]，在该上限是一个近似为无穷大的一系列求和。在这里，y是响应。
参数：tolerance
Positive numeric. When all terms are less than this then the series is deemed to have converged.
正数值。当所有条款都低于这一标准，那么该系列将被视为已融合。
参数：zero
An integer-valued vector specifying which linear/additive predictors are modelled as intercepts only. If used, the value must be 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。如果使用，则该值必须是从集合{1,2}。
Details
详细信息----------Details----------
A random variable Y has a 2-parameter beta-geometric distribution if P(Y=y) = prob * (1-prob)^y for y=0,1,2,... where prob are generated from a standard beta distribution with shape parameters shape1 and shape2. The parameterization here is to focus on the parameters prob and phi = 1/(shape1+shape2), where phi is shape. The default link functions for these ensure that the appropriate range of the parameters is maintained. The mean of Y is E(Y) = shape2 / (shape1-1) = (1-prob) / (prob-phi).
随机变量Y如果P(Y=y) = prob * (1-prob)^yy=0,1,2,...其中prob生成一个标准的Beta分布的形状参数shape12几何分布参数β-和shape2。这里是参数化的参数prob和phi = 1/(shape1+shape2)phi是shape。默认链接的功能，这些保证的参数保持在适当的范围内。 Y的平均E(Y) = shape2 / (shape1-1) = (1-prob) / (prob-phi)。
The geometric distribution is a special case of the beta-geometric distribution with phi=0 (see geometric). However, fitting data from a geometric distribution may result in numerical problems because the estimate of log(phi) will 'converge' to -Inf.
几何分布是一个特殊的情况下，β-几何分布phi=0（见geometric）。然而，从几何分布的数据拟合，可能会导致数值问题，因为估计log(phi)会“衔接”-Inf。
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。
注意----------Note----------
The first iteration may be very slow; if practical, it is best for the weights argument of vglm etc. to be used rather than inputting a very long vector as the response, i.e., vglm(y ~ 1, ..., weights=wts) is to be preferred over vglm(rep(y, wts) ~ 1, ...). If convergence problems occur try inputting some values of argument ishape.
第一次迭代的速度可能会很慢，如果可行的话，最好是为weights使用，而不是作为响应，即输入一个很长的向量，vglm等vglm(y ~ 1, ..., weights=wts)参数是优于vglm(rep(y, wts) ~ 1, ...)。如果衔接出现问题，尝试输入一些参数ishape值。
If an intercept-only model is fitted then the misc slot of the fitted object has list components shape1 and shape2.
如果仅截距模型拟合那么misc插槽的拟合对象的列表组件shape1和shape2。
（作者）----------Author(s)----------
T. W. Yee
参考文献----------References----------
Testing goodness of fit of the geometric distribution: an application to human fecundability data. Journal of Modern Applied Statistical Methods, 4, 425–433.
参见----------See Also----------
geometric, betaff, rbetageom.
geometric，betaff，rbetageom。
实例----------Examples----------
bg.data = data.frame(y = 0:11, wts = c(227,123,72,42,21,31,11,14,6,4,7,28))
fit = vglm(y ~ 1, betageometric, bg.data, weight = wts, trace = TRUE)
fitg = vglm(y ~ 1, geometric, bg.data, weight = wts, trace = TRUE)
coef(fit, matrix = TRUE)
Coef(fit)
sqrt(diag(vcov(fit, untransform = TRUE)))
fit@misc$shape1
fit@misc$shape2
# Very strong evidence of a beta-geometric:[β-几何非常有力的证据：]
pchisq(2*(logLik(fit) - logLik(fitg)), df = 1, lower.tail = FALSE)
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。
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发表于 2012-10-1 15:26:20
