R语言 RSiena包 sienaTimeTest()函数中文帮助文档(中英文对照)

loveR

sienaTimeTest(RSiena)
sienaTimeTest()所属R语言包：RSiena

                                        Functions to assess and account for time heterogeneity of parameters
                                         功能评估和说明的时间异质性的参数

                                         译者：生物统计家园网 机器人LoveR

描述----------Description----------

Takes a sienaFit object from a siena07 estimation and tests the addition of dummy parameters at waves m=2...(M-1) through the score type test of Schweinberger (2007b). Tests for joint significance, parameter-wise significance, individual significance, and one step estimation of the unrestricted model parameters are returned in a list.
一个sienaFit对象从一个siena07的估计和虚设参数的测试中，除了在波m=2...(M-1)得分Schweinberger（2007年b）型式试验。返回列表中的联合显着性，参数的意义，个人的意义，并一步步的无限制模型参数估计的测试。

After assessing time heterogeneity, effects objects can be modified via the timeDummy column. Simply type the periods which you would like to have time dummied separated by commas into this column. Using the timeDummy column within the effects object, you may specify which time dummy interacted parameters are to be estimated.
评估时间异质性，影响对象可以修改通过timeDummy列。只需键入你想有时间空置的用逗号分隔此列的期限内。使用timeDummy柱内的影响对象，你可以指定时间的虚拟互动的参数进行估计。

If you wish to use this function with sienaFit objects which use the finite differences method of derivative estimation, or which use maximum likelihood estimation, you must request the derivatives to be returned by wave using the byWave=TRUE option to siena07.
如果你想使用此函数的导数有限差分法，或使用最大似然估计的sienaFit对象，使用，您必须请求返回的衍生工具的使用byWave=TRUE选项siena07的波。


用法----------Usage----------


sienaTimeTest(sienaFit, effects=NULL, condition=FALSE)



参数----------Arguments----------

参数：sienaFit
A sienaFit object returned by siena07.  
返回sienaFitAsiena07对象。


参数：effects
Optional vector of effect numbers to test. Use the number on the print of the sienaFit object.
可选的矢量效果的数字进行测试。使用数字打印的sienaFit对象。


参数：condition
Whether to orthogonalize individual score tests against base effects and un-estimated dummy terms or just base effects.
是否正交个人的得分测试，对基数效应和联合国估计虚设条款或只是基数效应。


Details

详细信息----------Details----------

This test follows the score type test of Schweinburger (2007b) as implemented by Lospinoso et. al. (2010) by using statistics already calculated at each wave to populate vectors of partitioned moment functions corresponding to a restricted model (the model that has been fit by sienaFit Object) and an unrestricted model (which contains dummies for m=2...(M-1)). A covariance matrix of these statistics is calculated, and a delta matrix is constructed through the score functions' outer products with these statistics. Through an orthogonalization and a Delta method of approximation, the variance-covariance structure of the dummy statistics is calculated, and appropriate statistical tests can be used.
这项测试的得分如下型式试验的Schweinburger（2007年b）实施Lospinoso等。人。 （2010）利用已经计算在每一波的统计数据来填充向量片刻功能分区对应一个受限制的模型（已符合sienaFit对象模型）和无限制模式（其中包含假人<X >）。这些统计数据的协方差矩阵被计算，并且通过与这些统计信息的得分函数的外积的delta矩阵构成。虚设统计数字的方差 - 协方差结构通过正交和德尔塔的近似方法，计算，可以使用适当的统计测试。

If it is determined that a time heterogeneity occurs for any number of time periods or effects (or any combination therein), the timeDummy column provides facilities within a sienaFit object to quickly adjust the model and re-estimate in the usual way. The includeTimeDummy function can be used to add the desired dummies entries to the effects object.
如果它被确定为任何数目的时间段或效果（或其中的任何组合），发生的时间异质性timeDummy列提供sienaFit对象内的设施来快速调整的模型和重新估计在通常的方式。 includeTimeDummy函数可以用来添加所需的假人的影响对象的条目。


值----------Value----------

sienaTimeTest Returns a list containing many items, including the following:
sienaTimeTest返回一个列表，其中包含了许多项目，包括以下内容：


参数：JointTest
A chi^2 test for joint significance of the dummies.
Achi^2测试联合意义的假人。


参数：ParameterTest
A chi^2 test for joint significance across dummies for each separate effect.
Achi^2测试假人为每个单独的效果之间的联合显着。


参数：IndividualTest
A matrix displaying initial estimates, one step estimates, and a p-value for H0: the unrestricted parameters are equal to zero.
的矩阵显示的初始估计，一个步骤的估计，和p-值H0:的无限制的参数都等于零。


（作者）----------Author(s)----------


Josh Lospinoso



参考文献----------References----------

for general information on RSiena.
R.M. "Assessing and Accounting for Time Heterogeneity in Stochastic Actor Oriented Models". Advances in Data Analysis and Computation. Special Issue on Social Networks. Submitted. Available from http://www.stats.ox.ac.uk/~lospinos/.
data: Monte carlo-based derivative estimation. Comput. Stat. Data Anal., 51(9):4465-4483, 2007.  ISSN 0167-9473.
Goodness of Fit. PhD thesis, University of Groningen, 2007.

参见----------See Also----------

siena07, plot.sienaTimeTest,
siena07，plot.sienaTimeTest，


实例----------Examples----------


## Estimate a restricted model[＃估计受限制的模型]
mymodel <- sienaModelCreate(fn=simstats0c, nsub=2, n3=100)
mynet1 <- sienaNet(array(c(s501, s502, s503), dim=c(50, 50, 3)))
mydata <- sienaDataCreate(mynet1)
myeff <- getEffects(mydata)
myeff <- includeEffects(myeff, transTrip, balance)
ans <- siena07(mymodel, data=mydata, effects=myeff, batch=TRUE)

## Conduct the score type test to assess whether heterogeneity is present.[＃进行测试，以评估是否存在异质性的计分方式。]
tt <- sienaTimeTest(ans)

## Suppose that we wish to include two time dummies.[＃假设我们希望包括两个假人。]
## Add them in the following way:[＃通过以下方式：]
myeff <- includeTimeDummy(myeff, recip, balance, timeDummy="2")
ans2 <- siena07(mymodel, data=mydata, effects=myeff, batch=TRUE)

## Re-assess the time heterogeneity[＃重新评估的时间异质性]
tt2 <- sienaTimeTest(ans2)

## And so on..[＃..]

## A demonstration of the plotting facilities, on a larger dataset:[＃A的标绘设施的示范，在更大的数据集：]
## Not run: [＃不运行：]
mymodel <- sienaModelCreate(fn=simstats0c, nsub=4, n3=500)
mynet1 <- sienaNet(array(c(s501, s502, s503, s501, s503, s502), dim=c(50, 50, 6)))
mydata <- sienaDataCreate(mynet1)
myeff <- getEffects(mydata)
myeff <- includeEffects(myeff, transTrip, balance)
myeff <- includeTimeDummy(myeff, recip, timeDummy="2,3,5")
myeff <- includeTimeDummy(myeff, balance, timeDummy="4")
myeff <- includeTimeDummy(myeff, density, timeDummy="all")
ansp <- siena07(mymodel, data=mydata, effects=myeff, batch=FALSE)
ttp <- sienaTimeTest(ansp)

## Pairwise plots show[＃成对图显示]
plot(ttp, pairwise=TRUE)

## Time test plots show[时间测试图显示]
plot(ttp, effects=1:4, dims=c(2,2))

## End(Not run)[＃（不执行）]
## A demonstration of RateX heterogeneity. Note that rate[＃RateX异质性的示范。需要注意的是速度]
## interactions are not implemented in general, just for[＃交互，总体执引号况，只是]
## Rate x cCovar.[＃率X cCovar。]
## Not run: [＃不运行：]
mymodel <- sienaModelCreate(fn=simstats0c, nsub=2, n3=100)
mynet1 <- sienaNet(array(c(s501, s502, s503), dim=c(50, 50, 3)))
myccov <- coCovar(s50a[,1])
mydata <- sienaDataCreate(mynet1, myccov)
myeff <- getEffects(mydata)
myeff <- includeEffects(myeff, transTrip, balance)
myeff <- includeTimeDummy(myeff, RateX, type="rate",
                        interaction1="myccov")
ans <- siena07(mymodel, data=mydata, effects=myeff, batch=TRUE)

## 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。