ResampleExploreSpawML(spacom)
ResampleExploreSpawML()所属R语言包：spacom
Exploratory spatially weighted multilevel analysis with stratified resampling
多层次的分析与探索性空间加权分层重采样
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Performs exploratory multilevel analysis with spatially weighted context data for a series of different bandwidth values. Provides robust point estimates and standard errors based on stratified bootstrap resampling.
执行探索多层次的空间加权上下文数据分析与一系列不同的带宽值。提供强大的点估计和标准的基础上分层引导重采样的错误。
用法----------Usage----------
ResampleExploreSpawML(individual.level.data, contextual.name,
contextual.data, context.id, nb.resamples, formula, distance.matrix,
multilevel.bandwidths, individual.weight.name = NULL,
aggregation.function = "mean", confidence.intervals = c(0.95),
individual.sample.seed = NULL, contextual.sample.seed = NULL, kernel =
NULL)
参数----------Arguments----------
参数：individual.level.data
A data.frame containing the individual level data. The data must be numeric (logical, integer, or plain numeric). There may not be any missing values, NaNs, NULLs or NAs.
Adata.frame个人层面上的数据。数据必须是数字（logical，integer，或纯numeric）。可能没有任何遗漏值，NaN，NULLs或NA的。
参数：contextual.name
A name of contextual variable to be weighted.
出了名的上下文变量进行加权。
参数：contextual.data
A data.frame containing the micro-level data to generate contextual indicators by aggregation. May be NULL, in which case the individual data is used. The data must be numeric (logical, integer, or plain numeric). There may not be any missing values, NaNs, NULLs or NAs. By default set to NULL.
Adata.frame包含微观层面的数据产生关联的聚集指标。可能是NULL，在这种情况下，使用单个数据。数据必须是数字（logical，integer，或纯numeric）。可能没有任何遗漏值，NaN，NULLs或NA的。默认设置为NULL。
参数：context.id
The name of the context ID variable.
作为上下文ID的变量的名称。
参数：nb.resamples
A number of resamples to be evaluated. By default set to 1000.
许多重新采样进行评估。默认情况下设置为1000。
参数：formula
Formula description of the model.
公式描述的模式。
参数：distance.matrix
A square matrix of dimension n by n, where n is the number of contextual units.
方阵尺寸n by n，其中n是上下文相关单位的数量。
参数：multilevel.bandwidths
A vector of scalar numeric values specifying the bandwidth h
Avector标量数字值指定的带宽h，，
参数：individual.weight.name
A name of optional design weight at the individual level used for aggregation (for example, for a weighted mean). By default set to NULL.
用于聚集（例如，用于一个加权均值）在个体水平上的可选设计重量的名称。默认设置为NULL。
参数：aggregation.function
A name of aggregation function. Function takes either <ol> 1 argument in which case the corresponding individual design weight is NULL,
聚合函数的名称。功能需要或者<OL>的1个参数，在这种情况下，相应的个性化的设计重量是NULL，
2 arguments in which case the second argument is taken from the corresponding individual design weight. Defaults to "mean". </ol>
在这种情况下，第二个参数是从相应的个性化设计重量两个参数。默认为"mean"的。 </ OL>
参数：confidence.intervals
A vector of confidence intervals. Defaults to c(.95) which corresponds to 95 %.
Avector的置信区间。默认为c(.95)对应于95％。
参数：individual.sample.seed
Seed used to generate the random sampling of the individual data Is one of three things <ol> NULL, in which case whatever the current random seed is is used
种子用于生成的个别数据的随机抽样是<OL>NULL，在这种情况下，不管当前的随机种子使用的三件事情之一
an integer, which will be used to set the random seed. This allows reproducible random samples
的integer，将用于设置随机种子。这允许重复的随机样本
a saved .Random.seed which allows reproducible random samples as well. The reason why both 2 and 3 are present is because .Random.seed can be saved a posteriori. </ol> Defaults to NULL.
已保存的.Random.seed可重现的随机样本，以及。为什么2和3都存在的原因是因为.Random.seed可以保存后验。 </ OL>默认值到NULL。
参数：contextual.sample.seed
Seed used to generate the random sampling of the contextual data Is one of three things <ol> NULL, in which case whatever the current random seed is is used
种子用于生成随机抽样的上下文数据是<OL>NULL，在这种情况下，无论目前的随机种子使用的三件事情之一
an integer, which will be used to set the random seed. This allows reproducible random samples
的integer，将用于设置随机种子。这允许重复的随机样本
a saved .Random.seed which allows reproducible random samples as well. The reason why both 2 and 3 are present is because .Random.seed can be saved a posteriori. </ol> Defaults to NULL
已保存的.Random.seed可重现的随机样本，以及。为什么2和3都存在的原因是因为.Random.seed可以保存后验。 </ OL>默认值NULL
参数：kernel
A function applied to the distance matrix. By default NULL, in which case the kernel function <p align="center">w_ij = f(d, h) = (1/2)^((d_ij/h)^2)
一个功能应用到距离矩阵。缺省情况下NULL，在这种情况下，核函数<p ALIGN="CENTER">w_ij = f(d, h) = (1/2)^((d_ij/h)^2)
is used, where w_ij, d_ij, hare elements of the weight matrix W, of the distance matrix D and the bandwidth h. User-supplied kernel functions have to take 2 arguments and return a matrix of the same dimension as the first argument.
时，其中w_ij, d_ij, h的元素的权重矩阵W，距离矩阵D和带宽h中。用户提供的核心功能有2个参数作为第一个参数，并返回相同尺寸的矩阵。
（作者）----------Author(s)----------
Till Junge, Sandra Penic, Guy Elcheroth
实例----------Examples----------
# Exploratory spatially weighted multilevel analysis, with resampled[探索空间的加权多层次的分析，与重采样]
# both individual level indicators and contextual predictors for[一级指标包括个人和上下文的预测]
# aggregation. Accepts only one contextual predictor. Predicting[聚集。只接受一个情境的预测。预测]
# collective guilt acceptance. Contextual predictor weighted with[集体内疚验收。上下文预测加权]
# geographical proximity weights, h=50,100,200. [GEO上的接近权重，H = 50100200。]
# load individual level data, remove collective guilt assignment for the[加载个体层面的数据，除去集体罪责分配]
# data frame, and remove NA's [数据框，并删除NA]
data(traces_ind)
traces_ind <- traces_ind[,-7]
traces_ind <- na.exclude(traces_ind)
# load contextual indicator for aggregation[加载上下文聚集指标]
data(traces_event)
# load distance matrix [负载距离矩阵]
data(d_geo)
acc_homog <- ResampleExploreSpawML(individual.level.data=traces_ind,
contextual.name="w_all", contextual.data=traces_event,
context.id="area", nb.resamples=5,formula=cg_acc ~ victim_d + comb_d +
male + age_1990 + high_school + higher_edu + (1|area),
distance.matrix=d_geo, multilevel.bandwidths=c(50,100,200))
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。
|
发表于 2012-9-30 12:18:31
