fss2dfun(SpatialVx)
fss2dfun()所属R语言包：SpatialVx
Functions to calculate various verification statistics on possibly neighborhood smoothed fields.
函数来计算不同的检验统计上可能是附近的平滑领域。
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Functions to calculate various verification statistics on possibly neighborhood smoothed fields. Used by hoods2d, but can be called on their own.
函数来计算不同的检验统计上可能是附近的平滑领域。用于的hoods2d，但可以调用自己的。
用法----------Usage----------
fss2dfun(sPy, sPx, subset = NULL, verbose = FALSE)
fuzzyjoint2dfun(sPy, sPx, subset = NULL)
MinCvg2dfun(sIy, sIx, subset = NULL)
multicon2dfun(sIy, Ix, subset = NULL)
pragmatic2dfun(sPy, Ix, mIx = NULL, subset = NULL)
upscale2dfun(sYy, sYx, threshold = NULL, which.stats = c("rmse", "bias", "ts", "ets"), subset = NULL)
参数----------Arguments----------
参数：sPy
n X m matrix giving a smoothed binary forecast field.
N×M矩阵给一个平滑的二进制预测字段。
参数：sPx
n X m matrix giving a smoothed binary observed field.
N×M矩阵给一个平滑的二进制观测场。
参数：sIy
n X m matrix giving a binary forecast field.
N×M矩阵给出一个二进制预测字段。
参数：sIx
n X m matrix giving a binary observed field (the s indicates that the binary field is obtained from a smoothed field).
N×M矩阵，观察到一个二进制字段（s表示二进制字段获得的从平滑的字段）。
参数：Ix
n X m matrix giving a binary observed field.
N×M矩阵给出一个二进制的观察视野。
参数：mIx
(optional) single numeric giving the base rate. If NULL, this will be calculated by the function. Simply a computation saving step if this has already been calculated.
（可选）单个数字给予基准利率。如果为NULL，这将是由该函数计算。简单节约的计算步骤，如果这已经计算。
参数：sYy
n X m matrix giving a smoothed forecast field.
N×M矩阵给一个平滑的预测字段。
参数：sYx
n X m matrix giving a smoothed observed field.
N×M矩阵给一个平滑的观察视野。
参数：threshold
(optional) numeric vector of length 2 giving the threshold over which to calculate the verification statistics: bias, ts and ets. If NULL, only the rmse will be calculated.
（可选）数字矢量长度为2给出阈值以上计算检验统计：偏置，TS和ETS。如果为NULL，唯一的均方根误差的计算方法。
参数：which.stats
character vector naming which statistic(s) should be caluclated for upscale2dfun.
字符向量命名统计（）应caluclated，为upscale2dfun。
参数：subset
(optional) numeric indicating over which points the summary scores should be calculated. If NULL, all of the points are used.
（可选）数字说明点总结成绩，应计算。如果为NULL，所有的点都使用。
参数：verbose
logical, should progress information be printed to the screen?
逻辑的发展，应以信息打印到屏幕上？
Details
详细信息----------Details----------
These are modular functions that calculate the neighborhood smoothing method statistics in spatial forecast verification (see, e.g., Ebert, 2008, 2009; Gilleland et al., 2009, 2010; Roberts and Lean,2008). These functions take fields that have already had the neighborhood smoothing applied (e.g., using kernele2d) when appropriate. They are called by hoods2d, so need not be called by the user, but they can be.
这些模块化的功能附近平滑的空间预报检验方法统计计算（见，例如，艾伯特，2008年，2009年Gilleland等人，2009年，2010年罗伯茨和精益生产，2008年）。这些函数领域，已经有附近的平滑应用（例如，使用kernele2d）在适当的时候。他们被称为hoods2d，所以不需要由用户调用，但他们可以。
值----------Value----------
In the case of fss2dfun, a single numeric giving the FSS value is returned. In the other cases, list objects are returned with one or more of the following components, depending on the particular function.
的情况下，fss2dfun，一个单一的数字给FSS值返回。在其他情况下，返回与以下组件中的一个或多个列表对象，这取决于在特定的功能。
参数：fuzzy
fuzzyjoint2dfun returns a list with this list as one component. The list component fuzzy has the components: pod, far and ets.
fuzzyjoint2dfun返回一个列表，该列表中的一个组成部分。列表组件模糊的组成部分：布丁，远不及ETS。
参数：joint
fuzzyjoint2dfun returns a list with this list as one component. The list component joint has the components: pod, far and ets.
fuzzyjoint2dfun返回一个列表，该列表中的一个组成部分。列表组件共同具有的组成部分：布丁，远不及ETS。
参数：pod
numeric giving the probability of detection, or hit rate.
数字给出概率的检测，或命中率。
参数：far
numeric giving the false alarm ratio.
数字的误报率。
参数：ets
numeric giving the equitable threat score, or Gilbert Skill Score.
数字给予公平的威胁得分，吉尔伯特技能的分数。
参数：f
numeric giving the false alarm rate.
数字的误报率。
参数：hk
numeric giving the Hanssen-Kuipers statistic.
数字给的汉森奎伯斯统计。
参数：bs
Brier Score
野蔷薇分数
参数：bss
Brier Skill Score. The pragmatic2dfun returns the bs and bss values. The Brier Skill Score here uses the mean square error between the base rate and the Ix field as the reference forecast.
野蔷薇技能分数。 pragmatic2dfun返回的BS和BSS的值。石南木技能分数在这里使用的均方误差作为参考预测的基本速率和Ix的字段之间。
参数：ts
numeric giving the threat score.
数字的威胁得分。
参数：bias
numeric giving the frequency bias.
数字的频率偏差。
（作者）----------Author(s)----------
Eric Gilleland
参考文献----------References----------
<h3>See Also</h3>
实例----------Examples----------
x <- y <- matrix( 0, 100, 100)
x[ sample(1:100, 10), sample(1:100, 10)] <- 1
y[ sample(1:100, 20), sample(1:100, 20)] <- 1
Px <- kernel2dsmooth( x, kernel.type="boxcar", n=9, xdim=c(100, 100))
Py <- kernel2dsmooth( y, kernel.type="boxcar", n=9, xdim=c(100, 100))
par( mfrow=c(2,2))
image( x, col=c("grey", "darkblue"), main="Simulated Observed Events")
image( y, col=c("grey", "darkblue"), main="Simulated Forecast Events")
image( Px, col=c("grey", tim.colors(256)), main="Forecast Event Frequencies (9 nearest neighbors)")
image( Py, col=c("grey", tim.colors(256)), main="Smoothed Observed Events (9 nearest neighbors)")
fss2dfun( Py, Px)
## Not run: [＃不运行：]
data(pert004)
data(pert000)
fbin <- obin <- matrix(0, 601, 501)
fbin[ pert004 >= 12] <- 1
obin[ pert000 >= 12] <- 1
Pf <- kernel2dsmooth( fbin, kernel.type="boxcar", n=33, xdim=c(601, 501))
Po <- kernel2dsmooth( obin, kernel.type="boxcar", n=33, xdim=c(601, 501))
fss2dfun(Pf, Po)
fuzzyjoint2dfun(Pf, Po)
Pe <- 1/(33^2) # At least one event in the neighborhood.[至少在附近的一个事件。]
MinCvg2dfun(Pf >= Pe, Po >= Pe)
multicon2dfun(Pf >= Pe, obin)
pragmatic2dfun(Pf, obin, mIx=mean( obin, na.rm=TRUE))
Sf <- kernel2dsmooth( pert004, kernel.type="boxcar", n=33, xdim=c(601, 501))
So <- kernel2dsmooth( pert000, kernel.type="boxcar", n=33, xdim=c(601, 501))
upscale2dfun( Sf, So, threshold=12)
## 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 2012-9-30 12:55:37
