gamma2.ab(VGAM)
gamma2.ab()所属R语言包：VGAM
2-parameter Gamma Distribution
2参数Gamma分布
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Estimates the 2-parameter gamma distribution by maximum likelihood estimation.
估计2个参数的伽玛分布的最大似然估计。
用法----------Usage----------
gamma2.ab(lrate = "loge", lshape = "loge",
erate = list(), eshape = list(),
irate = NULL, ishape = NULL, expected = TRUE, zero = 2)
参数----------Arguments----------
参数：lrate, lshape
Link functions applied to the (positive) rate and shape parameters. See Links for more choices.
链接功能施加到的（正）率和形状参数。见Links更多的选择。
参数：erate, eshape
List. Extra arguments for the links. See earg in Links for general information.
列表。额外的参数的链接。见earg中Links的一般信息。
参数：expected
Logical. Use Fisher scoring? The default is yes, otherwise Newton-Raphson is used.
逻辑。使用费希尔得分？默认为yes，否则牛顿 - 拉夫逊。
参数：irate, ishape
Optional initial values for rate and shape. A NULL means a value is computed internally. If a failure to converge occurs, try using these arguments.
率和形状的可选的初始值。 ANULL是指在内部计算的值。如果收敛失败时，尝试使用这些参数。
参数：zero
An integer specifying which linear/additive predictor is to be modelled as an intercept only. If assigned, the single value should be either 1 or 2 or NULL. The default is to model shape as an intercept only. A value NULL means neither 1 or 2.
一个整数，指定线性/添加剂的预测中是被定义成仅截距。如果分配的，单一的值应为1或2或NULL。默认是模拟shape只为拦截。值NULL是指既不1或2。
Details
详细信息----------Details----------
The density function is given by
的密度函数由下式给出
for shape > 0, rate > 0 and y > 0. Here, gamma(shape) is the gamma function, as in gamma. The mean of Y is mu = shape/rate (returned as the fitted values) with variance sigma^2 = mu^2 /shape = shape/rate^2. By default, the two linear/additive predictors are eta1 = log(rate) and eta2 = log(shape).
shape > 0，rate > 0和y > 0。在这里，gamma(shape)是伽玛函数，如gamma。 y的均值是mu = shape/rate（返回的拟合值）与方差sigma^2 = mu^2 /shape = shape/rate^2。默认情况下，两个线性/添加剂的预测是eta1 = log(rate)和eta2 = log(shape)。
The argument expected refers to the type of information matrix. The expected information matrix corresponds to Fisher scoring and is numerically better here. The observed information matrix corresponds to the Newton-Raphson algorithm and may be withdrawn from the family function in the future. If both algorithms work then the differences in the results are often not huge.
参数expected是指信息矩阵的类型。预期的信息矩阵对应费舍尔得分，并在数值上更好地在这里。所观察到的信息矩阵对应的Newton-Raphson算法和家庭的功能在未来可能被撤销。如果这两种算法的工作，然后不同的结果往往是巨大的。
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和vgam。
注意----------Note----------
The parameters rate and shape match with the arguments rate and shape of rgamma. Often, scale = 1/rate is used.
参数rate和shape的参数rate和shapergamma匹配。通常情况下，scale = 1/rate使用。
If rate = 1 use the family function gamma1 to estimate shape.
如果rate = 1使用家庭功能gamma1估计shape。
（作者）----------Author(s)----------
T. W. Yee
参考文献----------References----------
the 2-parameter gamma distribution, e.g.,
Statistical Distributions, New York: Wiley-Interscience, Third edition.
参见----------See Also----------
gamma1 for the 1-parameter gamma distribution, gamma2 for another parameterization of the 2-parameter gamma distribution, bivgamma.mckay for a bivariate gamma distribution, expexp.
gamma11参数的伽玛分布，gamma2另外的2个参数的伽玛分布的参数设置，bivgamma.mckay的二元伽玛分布，expexp。
实例----------Examples----------
# Essentially a 1-parameter gamma[本质上是一个单参数的伽玛]
gdata <- data.frame(y = rgamma(n <- 100, shape = exp(1)))
fit1 <- vglm(y ~ 1, gamma1, gdata, trace = TRUE)
fit2 <- vglm(y ~ 1, gamma2.ab, gdata, trace = TRUE, crit = "c")
coef(fit2, matrix = TRUE)
Coef(fit2)
# Essentially a 2-parameter gamma[本质上是一个双参数的伽玛]
gdata <- data.frame(y = rgamma(n = 500, rate = exp(1), shape = exp(2)))
fit2 <- vglm(y ~ 1, gamma2.ab, gdata, trace = TRUE, crit = "c")
coef(fit2, matrix = TRUE)
Coef(fit2)
summary(fit2)
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 15:35:28
