CVresiduals.qqnorm(SpatioTemporal)
CVresiduals.qqnorm()所属R语言包：SpatioTemporal
QQ-norm and Scatterplots for Data and Residual Analysis
QQ规范和散点图数据和残差分析
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Does QQ-norm and scatterplots of observations or residuals from a cross-validation. The scatterplots are of observations against any reasonable covariate; examples of how todo scatter plots of observations against temporal smooths as well as geographic covariates are given.
请问QQ规范和交叉验证的意见或残留散点图。散点图是观测的任何合理的协TODO散点图观测对时间的平滑，以及GEO协变量的例子。
用法----------Usage----------
CVresiduals.qqnorm(res, I.season =
as.factor(rep("obs", length(res))), I.type = NA,
main = "All Data", norm = FALSE, legend = TRUE, ...)
CVresiduals.scatter(res, LUR, I.season =
as.factor(rep("obs",length(res))), I.type = NA,
xlab = "", main = "All Data", legend = TRUE,
df = 10, ...)
参数----------Arguments----------
参数：res
Vector of observations or residuals to plot. Could be one of <br> mesa.data$obs$obs, mesa.data.model$obs$obs, <br> predCV$pred.obs[,"pred"], statsCV$res, or <br> statsCV$res.norm. <br> Here predCV and statsCV are outputs from predictCV and <br> summaryStatsCV, respectively.
向量的观测或残差图的。可能是一个的参考mesa.data$obs$obs，mesa.data.model$obs$obs，参考predCV$pred.obs[,"pred"]，statsCV$res，或参考statsCV$res.norm。参考这里predCV和statsCV是predictCV和<br> summaryStatsCV，输出。
参数：LUR
A vector of land-use-regressors or other variable of interest against which to plot the residuals. Can be obtained from mesa.data.model as, e.g. <br> mesa.data.model$X[[1]][mesa.data.model$obs$idx, 2]. To plot the residuals against the temporal trends take <br> LUR=mesa.data.model$F[,2].
一个向量的土地使用的的回归量或其他变量绘制残差的兴趣。可从mesa.data.model，例如参考mesa.data.model$X[[1]][mesa.data.model$obs$idx, 2]。要绘制的时间趋势的残差对<BR>LUR=mesa.data.model$F[,2]。
参数：I.season
A vector of factors with the same length as res. The factors are used to colour code the points in the plots. The default, with only one factor, gives the same colour to all points.
res具有相同长度的因素的向量。颜色代码的因素是用来点的田块。默认情况下，只有一个因素，给出了相同颜色的所有点。
参数：I.type
A vector of characters or factors with the same length as res. The factors are used to produce one plot with all the data and then subsequent plots including only data of one type. Each of these plots are still colour coded according to I.season. The default, NA, assumes no breakdown. Elements that are NA in I.type will be included in the initial all data plot, but not in any of the subsequent plots.
一种向量，字符或因素作为res具有相同的长度。的因素被用来制造一个图，所有的数据，然后随后的图，包括只有一种类型的数据。这些图仍然是颜色编码，根据I.season。默认情况下，NA，不承担任何故障。元素是NA将包括所有的数据在最初的图，但不是在任何随后的图I.type。
参数：xlab
Name on the x-axis, typically the name of the LUR component against which the data is being plotted.
在x-轴，通常的名称，对其中的数据是被描绘的LUR组件的名称。
参数：main
Title of the plots.
标题的图。
参数：norm
If TRUE assumes standardised data/residuals (i.e. Gaussian with mean=0 and var=1) and adds abline(0,1) to the qqnorm-plot, in addition to qqline.
TRUE如果假设标准化的数据/残差（即均值高斯= 0，而var = 1），并增加了abline(0,1)到qqnorm图，除了qqline的。
参数：legend
If TRUE add a legend describing the colour coding due to I.season in the lower right hand corner.
如果TRUE添加一个传说描述的颜色编码，由于I.season在右下角。
参数：df
Desired equivalent number of degrees of freedom for the fitted smooth spline, see smooth.spline.
期望中的同等数量的光滑样条拟合的自由度，看到smooth.spline。
参数：...
Arguments passed on to the plotting function (qqnorm or plot).
传递参数的绘图功能（qqnorm或plot）。
值----------Value----------
Does not return anything.
不返回任何值。
（作者）----------Author(s)----------
Johan Lindstr枚m
参见----------See Also----------
See createCV and estimateCV for cross-validation set-up and estimation.
createCV和estimateCV交叉验证设置和估计。
For computing CV statistics, see also predictNaive and compute.ltaCV; for further illustration see plotCV and summaryStatsCV.
对于计算CV统计，predictNaive和compute.ltaCV;为进一步说明，请参阅plotCV和summaryStatsCV。
实例----------Examples----------
##load data[＃加载数据]
data(mesa.data.model)
##create a vector dividing data into four seasons[＃创建一个矢量将数据分成四季]
I.season <- matrix(NA,length(mesa.data.model$obs$date),1)
I.season[months(mesa.data.model$obs$date) %in%
c("December","January","February"),1] <- "DJF"
I.season[months(mesa.data.model$obs$date) %in%
c("March","April","May"),1] <- "MAM"
I.season[months(mesa.data.model$obs$date) %in%
c("June","July","August"),1] <- "JJA"
I.season[months(mesa.data.model$obs$date) %in%
c("September","October","November"),1] <- "SON"
I.season <- factor(I.season,levels=c("DJF","MAM","JJA","SON"))
##create a vector dividing data into type (AQS or FIXED)[＃创建一个向量划分数据类型（AQS或固定）]
I.type <- as.character(mesa.data.model$location$type[
mesa.data.model$obs$idx])
##qq-plot of the observations[＃QQ图的意见]
par(mfrow=c(2,2),mar=c(2,2,2,.5),mgp=c(1.7,.6,0),pty="s")
CVresiduals.qqnorm(mesa.data.model$obs$obs, I.season, I.type)
##scatter plot of the observations against some of the LUR-covariates[对部分的土地使用权，协变量散点图的意见]
LUR <- mesa.data.model$X[[1]][mesa.data.model$obs$idx,]
par(mfrow=c(2,3),mar=c(3,2.5,2,.5),mgp=c(1.7,.6,0),pty="s")
##i=1 is the constant LUR, not very interesting[＃i = 1是恒定LUR，不是非常有趣的]
for(i in 2:4)
CVresiduals.scatter(mesa.data.model$obs$obs, LUR[,i], I.season,
xlab = colnames(LUR)[i])
##and against the temporal trends[＃对的时间趋势]
for(i in 2:3)
CVresiduals.scatter(mesa.data.model$obs$obs, mesa.data.model$F[,i],
I.season, xlab = colnames(mesa.data.model$F)[i])
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。
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发表于 2012-9-30 13:03:10
