zinegbinomial(VGAM)
zinegbinomial()所属R语言包：VGAM
Zero-Inflated Negative Binomial Distribution Family Function
零膨胀的的负二项分布家庭功能
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Fits a zero-inflated negative binomial distribution by full maximum likelihood estimation.
适合零膨胀负二项分布完整的最大似然估计。
用法----------Usage----------
zinegbinomial(lpstr0 = "logit", lmunb = "loge", lsize = "loge",
epstr0 = list(), emunb = list(), esize = list(),
ipstr0 = NULL, isize = NULL, zero = c(-1, -3),
imethod = 1, shrinkage.init = 0.95, nsimEIM = 250)
参数----------Arguments----------
参数：lpstr0, lmunb, lsize
Link functions for the parameters pstr0, the mean and k; see negbinomial for details, and Links for more choices. For the zero-deflated model see below.
链接功能的参数pstr0，平均和k;看到negbinomial和Links更多的选择。对于零瘪的模型，请参阅下文。
参数：epstr0, emunb, esize
List. Extra arguments for the respective links. See earg in Links for general information.
列表。额外的参数，相应的链接。见earg中Links的一般信息。
参数：ipstr0, isize
Optional initial values for pstr0 and k. The default is to compute an initial value internally for both. If a vector then recycling is used.
可选的初始值pstr0和k。默认值是为内部计算初始值。如果一个向量，然后再循环使用。
参数：imethod
An integer with value 1 or 2 or 3 which specifies the initialization method for the mean parameter. If failure to converge occurs try another value and/or else specify a value for shrinkage.init.
一个整数，值1或2或3指定的均值参数的初始化方法。如果收敛失败时，尝试另一种价值和/或其他指定的值shrinkage.init。
参数：zero
Integers specifying which linear/additive predictor is modelled as intercepts only. If given, their absolute values must be either 1 or 2 or 3. The default is the pstr0 and k parameters (both for each response). See CommonVGAMffArguments for more information.
整数指定，其中线性/添加剂的预测中拦截只为蓝本。如果给出，它们的绝对值必须为1或2或3。默认值是pstr0和k参数（每个响应）。见CommonVGAMffArguments更多信息。
参数：shrinkage.init, nsimEIM
See CommonVGAMffArguments for information.
见CommonVGAMffArguments的信息。
Details
详细信息----------Details----------
This function uses simulation and Fisher scoring, and is based on
此功能使用模拟和费舍尔得分，并根据
and for y=1,2,…,
和y=1,2,…，
The parameter phi satisfies 0 < phi < 1. The mean of Y is (1-phi)*munb (returned as the fitted values). By default, the three linear/additive predictors are (logit(phi), log(munb), log(k))^T. See negbinomial, another VGAM family function, for the formula of the probability density function and other details of the negative binomial distribution.
参数phi满足0 < phi < 1。平均Y是(1-phi)*munb（返回的拟合值）。默认情况下，三个线性/添加剂的预测是(logit(phi), log(munb), log(k))^T。 negbinomial，另一个VGAM家庭功能，为负二项分布的概率密度函数和其他细节的公式。
Independent multivariate responses are handled. If so then arguments ipstr0 and isize may be vectors with length equal to the number of responses.
独立的多变量响应的处理。如果是这样的话，那么参数ipstr0和isize可能是向量长度相等的响应数。
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。
警告----------Warning ----------
Numerical problems can occur, e.g., when the probability of zero is actually less than, not more than, the nominal probability of zero. Half-stepping is not uncommon. If failure to converge occurs, try using combinations of imethod, shrinkage.init, ipstr0, isize, and/or zero if there are explanatory variables.
数值可能会发生问题，例如，当实际上是零的概率小于，不超过标称零概率。半步的情况并不少见。如果收敛失败时，尝试使用组合imethod，shrinkage.init，ipstr0，isize，和/或zero，“如果有解释变量。
注意----------Note----------
For intercept-models, the misc slot has a component called pobs0 which is the estimate of P(Y=0). Note that P(Y=0) is not the parameter phi.
截距模型，misc插槽中有一种成分叫做pobs0这是估计P(Y=0)。注意，P(Y=0)是不是参数phi。
If k is large then the use of VGAM family function zipoisson is probably preferable. This follows because the Poisson is the limiting distribution of a negative binomial as k tends to infinity.
k如果大，则用VGAM家庭功能zipoisson可能是最好的。在此之前，因为泊松k趋向于无穷大的负二项分布的极限分布。
The zero-deflated negative binomial distribution might be fitted by setting lpstr0 = identity, albeit, not entirely reliably. See zipoisson for information that can be applied here. Else try the zero-altered negative binomial distribution (see zanegbinomial).
的零瘪负的二项分布可能安装通过设置lpstr0 = identity，虽然不完全可靠。见zipoisson信息，可用于在这里。其他尝试改变零负二项分布（见zanegbinomial“）。
（作者）----------Author(s)----------
T. W. Yee
参见----------See Also----------
Zinegbin, negbinomial, rpois, CommonVGAMffArguments.
Zinegbin，negbinomial，rpois，CommonVGAMffArguments。
实例----------Examples----------
# Example 1[例1]
ndata <- data.frame(x2 = runif(nn <- 1000))
ndata <- transform(ndata, pstr0 = logit(-0.5 + 1 * x2, inverse = TRUE),
munb = exp( 3 + 1 * x2),
size = exp( 0 + 2 * x2))
ndata <- transform(ndata,
y1 = rzinegbin(nn, mu = munb, size = size, pstr0 = pstr0),
y2 = rzinegbin(nn, mu = munb, size = size, pstr0 = pstr0))
with(ndata, table(y1)["0"] / sum(table(y1)))
fit <- vglm(cbind(y1, y2) ~ x2, zinegbinomial(zero = NULL), ndata)
coef(fit, matrix = TRUE)
summary(fit)
head(cbind(fitted(fit), with(ndata, (1 - pstr0) * munb)))
round(vcov(fit), 3)
# Example 2: RR-ZINB could also be called a COZIVGLM-ZINB-2[实施例2：RR-ZINB也可以被称为COZIVGLM-ZINB-2]
ndata <- data.frame(x2 = runif(nn <- 2000))
ndata <- transform(ndata, x3 = runif(nn))
ndata <- transform(ndata, eta1 = 3 + 1 * x2 + 2 * x3)
ndata <- transform(ndata, pstr0 = logit(-1.5 + 0.5 * eta1, inverse = TRUE),
munb = exp(eta1),
size = exp(4))
ndata <- transform(ndata,
y1 = rzinegbin(nn, pstr0 = pstr0, mu = munb, size = size))
with(ndata, table(y1)["0"] / sum(table(y1)))
rrzinb <- rrvglm(y1 ~ x2 + x3, zinegbinomial(zero = NULL), ndata,
Index.corner = 2, szero = 3, trace = TRUE)
coef(rrzinb, matrix = TRUE)
Coef(rrzinb)
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。
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发表于 2012-10-1 16:01:29
