adjust.parameter.count(RMark)
adjust.parameter.count()所属R语言包：RMark
Adjust count of estimated parameters
调整数的估计参数
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Modifies number of estimated parameters and the resulting AICc value for model selection.
修改数量的估计参数和模式的选择产生的国际会议中心值。
用法----------Usage----------
adjust.parameter.count(model, npar)
参数----------Arguments----------
参数：model
MARK model object
MARK模型对象
参数：npar
Value of count of estimated parameters
估计参数的计数值
Details
详细信息----------Details----------
When a model is run the parameter count determined by MARK is stored in results$npar and the AICc value is stored in results$AICc. If the argument adjust is set to TRUE in the call to run.mark.model and MARK determined that the design matrix was not full rank (i.e., the parameter count is less than the columns of the design matrix), then the parameter count from MARK is stored in results$npar.unadjusted and AICc in results$AICc.unadjusted and results$npar is set to the number of columns of the design matrix and results$AICc uses the assumed full rank value of npar. This function allows the parameter count to be reset to any value less than or equal to the number of columns in the design matrix. If results$npar.unadjusted exists it is kept as is. If it doesn't exist, then the current values of results$npar and results$AICc are stored in the .unadjusted fields to maintain the values from MARK, and the new adjusted values defined by the function argument npar are stored in results$npar and results$AICc. In the example below, the CJS model Phi(t)p(t) is fitted with the call to mark which defaults to adjust=TRUE. This is used to show how adjust.parameter.count can be used to adjust the count to 11 from the full rank count of 12. Alternatively, the argument adjust=FALSE can be added to prevent the adjustment which is appropriate in this case because Phi(6) and p(6) are confounded.
运行模型时，由MARK存储的参数计数results$npar和国际会议中心值存储在results$AICc。如果参数adjust设置为TRUE在调用run.mark.model和马克的设计矩阵满秩（即，参数计数小于设计矩阵的列），然后MARK的存储参数计数results$npar.unadjusted和国际会议中心results$AICc.unadjusted和results$npar的设计矩阵的列数设置为results$AICc使用承担全部等级值npar。此功能允许参数计数复位到任意值小于或等于设计矩阵中的列的数目。如果results$npar.unadjusted“存在，它保持原样。如果它不存在，那么的当前值results$npar和results$AICc.unadjusted领域保持的值MARK，和新的调整值定义的函数的参数都存储在npar都存储在results$npar和results$AICc。在下面的例子中，CJS模型披（T）P（t）的安装的调用mark默认为adjust=TRUE。这是用于，显示如何adjust.parameter.count可以用来调整计数到11，从12满秩计数。或者，参数adjust=FALSE可以加入，以防止调整，这是适当的岛（6）和p（6）在这种情况下，因为所混淆。
值----------Value----------
model: the mark model object with the adjustments made
型号：标记的模型对象的调整
（作者）----------Author(s)----------
Jeff Laake
参见----------See Also----------
run.mark.model,model.table
run.mark.model，model.table
实例----------Examples----------
data(dipper)
ptime=list(formula=~time)
Phitime=list(formula=~time)
dipper.phitime.ptime=mark(dipper,model.parameters=list(Phi=Phitime, p=ptime))
dipper.phitime.ptime=adjust.parameter.count(dipper.phitime.ptime,11)
dipper.phitime.ptime=mark(dipper,model.parameters=list(Phi=Phitime, p=ptime),
adjust=FALSE)
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 2012-9-26 23:37:43
