scan.test(spatstat)
scan.test()所属R语言包：spatstat
Spatial Scan Test
空间扫描测试
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Performs the Spatial Scan Test for clustering in a spatial point pattern, or for clustering of one type of point in a bivariate spatial point pattern.
进行空间扫描测试在一个空间点格局，或一种类型的点在一个二元空间点模式聚类的聚类。
用法----------Usage----------
scan.test(X, r, ...,
method = c("poisson", "binomial"),
nsim = 19,
baseline = NULL,
case = 2,
alternative = c("greater", "less", "two.sided"),
verbose = TRUE)
参数----------Arguments----------
参数：X
A point pattern (object of class "ppp").
点模式（类的对象"ppp"）。
参数：r
Radius of circle to use. A single number.
圆弧半径使用。一个数字。
参数：...
Optional. Arguments passed to as.mask to determine the spatial resolution of the computations.
可选。参数传递给as.mask，以确定其空间分辨率的计算。
参数：method
Either "poisson" or "binomial" specifying the type of likelihood.
无论是"poisson"或"binomial"指定类型的可能性。
参数：nsim
Number of simulations for computing Monte Carlo p-value.
P-值计算蒙特卡罗模拟数。
参数：baseline
Baseline for the Poisson intensity, if method="poisson". A pixel image or a function.
基线的泊松强度，如果method="poisson"。像素图像的功能。
参数：case
Which type of point should be interpreted as a case, if method="binomial". Integer or character string.
哪种类型的点的情况下应被解释为，如果method="binomial"。整数或字符串。
参数：alternative
Alternative hypothesis: "greater" if the alternative postulates that the mean number of points inside the circle will be greater than expected under the null.
另一种假设："greater"，如果替代假设的圆圈内点的平均数量将大于预期下空。
参数：verbose
Logical. Whether to print progress reports.
逻辑。无论是打印进度报告。
Details
详细信息----------Details----------
The spatial scan test (Kulldorf, 1997) is applied to the point pattern X.
的空间扫描测试（Kulldorf，1997）被施加到的点图案X。
In a nutshell,
概括地说，
If method="poisson" then a significant result would mean that there is a circle of radius r, located somewhere in the spatial domain of the data, which contains a significantly higher than expected number of points of X. That is, the pattern X exhibits spatial clustering.
如果method="poisson"然后一个显着的结果将意味着有一个圆的半径r，位于某处的空间域数据，其中包含了X点的数量显着高于预期。也就是说，图案X具有空间聚类。
If method="binomial" then X must be a bivariate (two-type) point pattern. By default, the first type of point is interpreted as a control (non-event) and the second type of point as a case (event). A significant result would mean that there is a circle of radius r which contains a significantly higher than expected number of cases. That is, the cases are clustered together, conditional on the locations of all points.
如果method="binomial"然后X必须是一个二元（2型）点模式。缺省情况下，所述第一类型的点被解释作为对照（无事件）和第二类型的点的情况下（事件）。一个显着的结果将意味着r其中包含一个显着高于预期的情况下，有一个圆的半径。也就是说，情况都聚集在一起，条件上的所有点的位置。
Following is a more detailed explanation.
下面是一个更详细的解释。
If method="poisson" then the scan test based on Poisson likelihood is performed (Kulldorf, 1997). The dataset X is treated as an unmarked point pattern. By default (if baseline is not specified) the null hypothesis is complete spatial randomness CSR (i.e. a uniform Poisson process). The alternative hypothesis is a Poisson process with one intensity beta1 inside some circle of radius r and another intensity beta0 outside the circle. If baseline is given, then it should be a pixel image or a function(x,y). The null hypothesis is an inhomogeneous Poisson process with intensity proportional to baseline. The alternative hypothesis is an inhomogeneous Poisson process with intensity beta1 * baseline inside some circle of radius r, and beta0 * baseline outside the circle.
如果method="poisson"然后基于泊松可能性进行扫描测试（Kulldorf，1997）。的数据集X被视为一个没有标记的点模式。默认情况下（如果baseline未指定）的零假设是完全空间随机性CSR（即一个统一的泊松过程）。另一种假设是与一个强度beta1里面有一些圆形的半径r和另一个beta0外循环强度的泊松过程。如果baseline给定的，那么它应该是一个像素图像或function(x,y)的。零假设是一个非齐次泊松过程的强度成正比，baseline。另一种假设是一个非齐次泊松过程的强度beta1 * baseline一些圆的半径内r和beta0 * baseline外面的圆圈。
If method="binomial" then the scan test based on binomial likelihood is performed (Kulldorf, 1997). The dataset X must be a bivariate point pattern, i.e. a multitype point pattern with two types. The null hypothesis is that all permutations of the type labels are equally likely. The alternative hypothesis is that some circle of radius r has a higher proportion of points of the second type, than expected under the null hypothesis.
如果method="binomial"然后进行扫描测试基于二项式可能性（Kulldorf，1997）。的数据集X点必须是一个二元模式，即一个多类型的模式有两种类型。零假设是所有类型标签的排列也同样有可能的。另一种假设是，有些圆的半径r有较高比例的第二点，比预期的零假设下。
The result of scan.test is a hypothesis test (object of class "htest") which can be plotted to report the results. The component p.value contains the p-value.
scan.test的结果是一个假设检验（类的对象"htest"）报告结果，可以绘制。组件p.value包含p价值。
The result of scan.test can also be plotted (using the plot method for the class "scan.test"). The plot is a pixel image of the Likelihood Ratio Test Statistic (2 times the log likelihood ratio) as a function of the location of the centre of the circle. This pixel image can be extracted from the object using as.im.
scan.test的结果也可以被绘制（使用方法的类的图"scan.test"“）。该图是一个像素的图像的似然比检验统计量（对数似然比的2倍）的圆的中心的位置的函数。这个像素的图像，可以提取使用as.im的对象。
值----------Value----------
An object of class "htest" (hypothesis test) which also belongs to the class "scan.test". Printing this object gives the result of the test. Plotting this object displays the Likelihood Ratio Test Statistic as a function of the location of the centre of the circle.
一个对象的类"htest"（假设检验）也属于类"scan.test"。打印这个对象给出了测试结果。绘图显示此对象的似然比检验统计量的函数圆心的位置。
（作者）----------Author(s)----------
Adrian Baddeley
<a href="mailto:Adrian.Baddeley@csiro.au">Adrian.Baddeley@csiro.au</a>
<a href="http://www.maths.uwa.edu.au/~adrian/">http://www.maths.uwa.edu.au/~adrian/</a>
and Rolf Turner
<a href="mailto:r.turner@auckland.ac.nz">r.turner@auckland.ac.nz</a>
参考文献----------References----------
A spatial scan statistic. Communications in Statistics — Theory and Methods 26, 1481–1496.
参见----------See Also----------
relrisk
relrisk
实例----------Examples----------
nsim <- if(interactive()) 19 else 2
data(redwood)
scan.test(redwood, 0.1, method="poisson", nsim=nsim)
data(chorley)
scan.test(chorley, 1, method="binomial", case="larynx", nsim=nsim)
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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发表于 2012-9-30 14:12:49
