calibrate.qrrvglm(VGAM)
calibrate.qrrvglm()所属R语言包：VGAM
Calibration for CQO, UQO and CAO models
CQO，UQO曹模型的校准
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Performs maximum likelihood calibration for constrained and unconstrained quadratic and additive ordination models (CQO and CAO models are better known as QRR-VGLMs and RR-VGAMs respectively).
执行最大似然校准约束和无约束的二次和添加剂协调模型（CQO与曹模型QRR-VGLMs和RR-VGAMs的的分别是更好地了解）。
用法----------Usage----------
calibrate.qrrvglm(object, newdata = NULL,
type = c("lv", "predictors", "response", "vcov", "all3or4"),
initial.vals = NULL, ...)
参数----------Arguments----------
参数：object
The fitted CQO/CAO model.
拟合的，CQO /航油模型的。
参数：newdata
A data frame with new response data (usually new species data). The default is to use the original data used to fit the model; however, the calibration may take a long time to compute because the computations are expensive.
与新的响应数据的数据框（通常是新物种数据）。缺省值是使用原来的使用的数据，以适应模型，然而，校准可能需要很长的时间来计算，因为计算是昂贵的。
参数：type
What type of result is to be returned. The first are the calibrated latent variables or site scores. This must be computed always. The "predictors" are the linear/quadratic or additive predictors evaluated at the calibrated latent variables or site scores. The "response" are the fitted means evaluated at the calibrated latent variables or site scores. The "vcov" are the estimated variance-covariance matrices of the calibrated latent variables or site scores. The "all3or4" is for all of them, i.e., all types. For CAO models, "vcov" is unavailable, so all 3 are returned. For CQO models, "vcov" is available, so all 4 are returned.
什么类型的结果将被返回。首先是校准的潜变量或网站分数。这必须计算总。 "predictors"是线性/二次或添加剂的预测，在经过校准的潜变量或网站评分进行评估。 "response"是在经过校准的潜变量或网站分数的拟合方法进行评估。 "vcov"校准的潜变量或网站分数的方差 - 协方差矩阵的估计。 "all3or4"是所有的人，即所有type的。曹模型，"vcov"是不可用的，因此，所有被返回。 CQO模型，"vcov"是可用的，所以所有4个返回。
参数：initial.vals
Initial values for the search. For rank-1 models, this should be a vector of length nrow(newdata), and for rank 2 models this should be a two column matrix with the number of rows equalling the number of rows in newdata. The default is a grid defined by arguments in calibrate.qrrvglm.control.
初始值进行搜索。对于排名-1型号，这应该是一个矢量的长度nrow(newdata)，和排名2个型号，这应该是一个两列的矩阵的行中的行数等于newdata。默认情况下是一个网格所定义的参数在calibrate.qrrvglm.control。
参数：...
Arguments that are fed into calibrate.qrrvglm.control.
的参数送入calibrate.qrrvglm.control。
Details
详细信息----------Details----------
Given a fitted regression CQO/CAO model, maximum likelihood calibration is theoretically easy and elegant. However, the method assumes that all species are independent, which is not really true in practice. More details and references are given in Yee (2012).
一个拟合的回归的CQO /曹模型，最大似然标定，理论上是简单和优雅的。然而，该方法假定所有物种是独立的，这是在实践中不是真的。更多的细节和参考文献中怡康（2012年）。
The function optim is used to search for the maximum likelihood solution. Good initial values are needed, and calibrate.qrrvglm.control allows the user some control over the choice of these.
功能optim是用于搜索的最大似然溶液。良好的初始值是必要的，calibrate.qrrvglm.control允许用户的选择一定程度上控制这些。
值----------Value----------
The argument type determines what is returned. If type = "all3or4" then all the type values are returned in a list, with the following components. Each component has length nrow(newdata).
确定什么是返回的参数type。如果type = "all3or4"然后type值中返回一个列表，有以下组件。每个组件都有长度nrow(newdata)。
参数：lv
Calibrated latent variables or site scores.
校准潜变量或现场评分。
参数：predictors
linear/quadratic or additive predictors. For example, for Poisson families, this will be on a log scale, and for binomial families, this will be on a logit scale.
线性/二次或添加剂的预测。例如，泊松家庭，这将是对数标度，和为二项式家庭，这将是在一个logit规模。
参数：response
Fitted values of the response, evaluated at the calibrated latent variables or site scores.
拟合值的响应，在经过校准的潜变量或网站评分进行评估。
参数：vcov
Estimated variance-covariance matrix of the calibrated latent variables or site scores. Actually, these are stored in an array whose last dimension is nrow(newdata).
估计方差 - 协方差矩阵的校准的潜变量或网站评分。其实，这些都是存储在数组中的最后一个维度是nrow(newdata)。
警告----------Warning ----------
This function is computationally expensive. Setting trace = TRUE to get a running log is a good idea.
这个函数在计算上是昂贵的。设置trace = TRUE得到的运行log是一个好主意。
注意----------Note----------
Despite the name of this function, UQO and CAO models are handled as well.
尽管此功能的名称，UQO曹模型以及处理。
（作者）----------Author(s)----------
T. W. Yee
参考文献----------References----------
On constrained and unconstrained quadratic ordination. Manuscript in preparation.
Calibration. In: Data Analysis in Community and Landscape Ecology by Jongman, R. H. G., ter Braak, C. J. F. and van Tongeren, O. F. R. (Eds.) Cambridge University Press, Cambridge.
参见----------See Also----------
calibrate.qrrvglm.control, calibrate, cqo, uqo, cao.
calibrate.qrrvglm.control，calibrate，cqo，uqo，cao。
实例----------Examples----------
## Not run: [＃不运行：]
hspider[,1:6] = scale(hspider[,1:6]) # Standardize the environmental variables[标准化的环境变量]
set.seed(123)
p1 = cqo(cbind(Pardlugu, Pardmont, Pardnigr, Pardpull, Zoraspin) ~
WaterCon + BareSand + FallTwig +
CoveMoss + CoveHerb + ReflLux,
family = poissonff, data = hspider, Rank = 1,
IToler = TRUE, Crow1positive = TRUE)
siteNos = 1:2 # Calibrate these sites[校准这些网站]
cp1 = calibrate(p1, new=data.frame(p1@y[siteNos,]), trace = TRUE)
## End(Not run)[＃（不执行）]
## Not run: [＃不运行：]
# Graphically compare the actual site scores with their calibrated values[图形方式比较实际的网站得分与他们的校准值]
persp(p1, main = "Site scores: solid=actual, dashed=calibrated",
label = TRUE, col = "blue", las = 1)
abline(v = lv(p1)[siteNos], lty = 1, col = 1:length(siteNos)) # actual site scores[现场实际成绩]
abline(v = cp1, lty = 2, col = 1:length(siteNos)) # calibrated values[校准值]
## End(Not run)[＃（不执行）]
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。
注3：如遇到不准确之处，请在本贴的后面进行回帖，我们会逐渐进行修订。
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发表于 2012-10-1 15:28:10
