glm(safeBinaryRegression)
glm()所属R语言包:safeBinaryRegression
Fitting Generalized Linear Models
拟合广义线性模型
译者:生物统计家园网 机器人LoveR
描述----------Description----------
This function overloads the glm function so that a check for the existence of the maximum likelihood estimate is computed before fitting a "glm" with a binary response.
此函数重载glm功能,使计算装修前一个二进制的反应“GLM”的支票,最大似然估计的存在。
用法----------Usage----------
glm(formula, family = gaussian, data, weights, subset, na.action, start = NULL, etastart, mustart, offset, control = glm.control(...), model = TRUE, method = "glm.fit", x = FALSE, y = TRUE, contrasts = NULL, ..., separation = c("find", "test"))
参数----------Arguments----------
参数:separation
either “find” or “test”. Both options prevent the model from being fit to binary data when the maximum likelihood estimate does not exist. Additionally, when separation = "find", the terms separating the sample points are identified when the maximum likelihood estimate is found not to exist.
“发现”或“测试”。这两个选项,防止模型是合适的二进制数据时的最大似然估计不存在。此外,当separation = "find",分离采样点的确定时,最大似然估计是不存在的。
参数:formula
see glm
看到glm
参数:family
see glm
看到glm
参数:data
see glm
看到glm
参数:weights
see glm
看到glm
参数:subset
see glm
看到glm
参数:na.action
see glm
看到glm
参数:start
see glm
看到glm
参数:etastart
see glm
看到glm
参数:mustart
see glm
看到glm
参数:offset
see glm
看到glm
参数:control
see glm
看到glm
参数:model
see glm
看到glm
参数:method
see glm
看到glm
参数:x
see glm
看到glm
参数:y
see glm
看到glm
参数:contrasts
see glm
看到glm
参数:...
see glm
看到glm
Details
详细信息----------Details----------
This function checks for the existence of the maximum likelihood estimate before the "glm" function is used to fit binary regression models by solving the linear program proposed in Konis (2007).
此功能检查前的最大似然估计的存在“GLM”功能,来拟合二元回归模型,通过求解线性规划在Konis(2007)提出。
值----------Value----------
See the return value for the glm function.
为glm函数的返回值。
(作者)----------Author(s)----------
Kjell Konis <a href="mailto:kjell.konis@epfl.ch">kjell.konis@epfl.ch</a>
参考文献----------References----------
Kjell Konis (2007). Linear programming algorithms for detecting separated data in binary logistic regression models. DPhil, University of Oxford http://ora.ouls.ox.ac.uk/objects/uuid:8f9ee0d0-d78e-4101-9ab4-f9cbceed2a2a
参见----------See Also----------
glm.
glm。
实例----------Examples----------
## A set of 4 completely separated sample points ##[#A组的4个完全分离的样品点##]
x <- c(-2, -1, 1, 2)
y <- c(0, 0, 1, 1)
## Not run: glm(y ~ x, family = binomial)[#不运行:GLM(Y,X,家庭=二项式)]
## A set of 4 quasicompletely separated sample points ##[#A组的4 quasicompletely分离的采样点##]
x <- c(-2, 0, 0, 2)
y <- c(0, 0, 1, 1)
## Not run: glm(y ~ x, family = binomial)[#不运行:GLM(Y,X,家庭=二项式)]
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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