negbinomial.size(VGAM)
negbinomial.size()所属R语言包：VGAM
Negative Binomial Distribution Family Function With Known Size
负二项分布家庭功能与已知的大小
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Maximum likelihood estimation of the mean parameter of a negative binomial distribution with known size parameter.
最大似然估计的平均负二项分布参数的已知大小的参数。
用法----------Usage----------
negbinomial.size(size = Inf, lmu = "loge", emu = list(), imu = NULL,
quantile.probs = 0.75, imethod = 1,
shrinkage.init = 0.95, zero = NULL)
参数----------Arguments----------
参数：size
Numeric, positive. Same as argument size of rnbinom. If the response is a matrix then this is recycled to a matrix of the same dimension, by row (matrix with byrow = TRUE).
数字的，积极的。同作为参数sizernbinom。如果响应是一个矩阵，那么这是再循环到具有相同维数的矩阵，按行（matrix与byrow = TRUE）。
参数：lmu, emu, imu
Same as negbinomial.
与negbinomial相同。
参数：quantile.probs
Same as negbinomial.
与negbinomial相同。
参数：imethod, zero
Same as negbinomial.
与negbinomial相同。
参数：shrinkage.init
Same as negbinomial.
与negbinomial相同。
Details
详细信息----------Details----------
This VGAM family function estimates only the mean parameter of the negative binomial distribution. See negbinomial for general information. Setting size = 1 gives what I call the NB-G (geometric model; see Hilbe (2011)). The default, size = Inf, corresponds to the Poisson distribution.
这VGAM家庭功能参数估计的平均负二项分布。见negbinomial一般信息。设置size = 1给了我所说的NB-G（几何模型;请参阅Hilbe（2011））。默认情况下，size = Inf，对应的泊松分布。
值----------Value----------
An object of class "vglmff" (see vglmff-class). The object is used by modelling functions such as vglm, rrvglm and vgam.
类的一个对象"vglmff"（见vglmff-class）。该对象被用于建模功能，如vglm，rrvglm和vgam。
注意----------Note----------
If lmu = "nbcanlink" in negbinomial.size() then the size argument here is placed inside the earg argument of nbcanlink() as a matrix with conformable size.
如果lmu = "nbcanlink"negbinomial.size()然后sizeearg参数参数被放置在nbcanlink()作为一个矩阵，贴合尺寸。
（作者）----------Author(s)----------
Thomas W. Yee
参考文献----------References----------
Negative Binomial Regression, 2nd Edition. Cambridge: Cambridge University Press.
Two-parameter reduced-rank vector generalized linear models. In preparation.
参见----------See Also----------
negbinomial, nbcanlink (NB-C model), quasipoissonff, poissonff, rnbinom.
negbinomial，nbcanlink（NB-C型号），quasipoissonff，poissonff，rnbinom。
实例----------Examples----------
# Simulated data with various multiple responses[模拟数据与多个不同的反应]
size1 = exp(1); size2 = exp(2); size3 = exp(0); size4 = Inf
ndata <- data.frame(x2 = runif(nn <- 1000))
ndata <- transform(ndata, eta1 = -1 - 2 * x2, # eta1 must be negative[ETA1必须负]
size1 = size1)
ndata <- transform(ndata,
mu1 = nbcanlink(eta1, earg = list(size = size1), inv = TRUE))
ndata <- transform(ndata,
y1 = rnbinom(nn, mu = mu1, size = size1), # NB-C[NB-C]
y2 = rnbinom(nn, mu = exp(2 - x2), size = size2),
y3 = rnbinom(nn, mu = exp(3 + x2), size = size3), # NB-G[NB-G]
y4 = rpois (nn, la = exp(1 + x2)))
# Also known as NB-C with size known (Hilbe, 2011)[也被称为NB-C尺寸已知的（Hilbe，2011）]
fit1 <- vglm(y1 ~ x2, negbinomial.size(size = size1, lmu = "nbcanlink"),
ndata, trace = TRUE, crit = "coef")
coef(fit1, matrix = TRUE)
head(fit1@misc$size) # size saved here[大小保存在这里]
fit2 <- vglm(cbind(y2, y3, y4) ~ x2,
negbinomial.size(size = c(size2, size3, size4)),
ndata, trace = TRUE)
coef(fit2, matrix = TRUE)
head(fit2@misc$size) # size saved here[大小保存在这里]
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 15:45:37
