conditional.quantile(verification)
conditional.quantile()所属R语言包：verification
Conditional Quantile Plot
有条件的分量图
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function creates a conditional quantile plot as shown in
这个函数创建一个分位数图所示
用法----------Usage----------
conditional.quantile(pred, obs, bins = NULL, thrs = c(10, 20), main,
参数----------Arguments----------
参数：pred
Forecasted value. ([n,1] vector, n = \# of forecasts)
预测值。 （[1]向量，n = \＃预测）
参数：obs
Observed value.([n,1] vector, n = \# of observations)
观测值。（[1]向量，n = \＃观察）
参数：bins
Bins for forecast and observed values. A minimum number of values are required to calculate meaningful statistics. So for variables that are continuous, such as temperature, it is frequently convenient to bin these values. ([m,1] vector, m = \# of bins)
回收桶的预测值与实测值。需要的最小数目的值计算出有意义的统计数据。因此，是连续的，如温度的变量，它常常是方便的为bin这些值。 （[M 1]向量，M = \＃箱）
参数：thrs
The minimum number of values in a bin required to calculate the 25th and 75th quantiles and the 10th and 90th percentiles respectively. The median values will always be displayed. ( [2,1] vector)
在bin值的最低数量要求，第25和第75位数，第10和第90百分位数分别计算。中值将始终显示。 （咪唑并[2,1]矢量）
参数：main
Plot title
图标题
参数：...
Plotting options.
打印选项。
值----------Value----------
This function produces a conditional.quantile plot. The $y$ axis represents the observed values, while the $x$ axis represents the forecasted values. The histogram along the bottom axis
这函数生成一个conditional.quantile的图。 $ Y轴代表的观测值，而$ X $轴表示预测值。沿底部轴的直方图
注意----------Note----------
In the example below, the median line extends beyond the range of the quartile or 10th and 90th percentile lines. This is because there are not enough points in each bin to calculate these quartile values.
在下面的例子中，超出范围的四分位数或第10和第90百分位线的中位线。这是因为没有足够的积分，在每个容器来计算这些四分位值。
（作者）----------Author(s)----------
Matt Pocernich <pocernic@rap.ucar.edu>
参考文献----------References----------
Verification of Temperature Forecasts,” Weather and Forecasting; December, 1989.
实例----------Examples----------
set.seed(10)
m<- seq(10, 25, length = 1000)
frcst <- round(rnorm(1000, mean = m, sd = 2) )
obs<- round(rnorm(1000, mean = m, sd = 2 ))
bins <- seq(0, 30,1)
thrs<- c( 10, 20) # number of obs needed for a statistic to be printed #1,4 quartile, 2,3 quartiles[2,3所需的OBS的统计要打印的＃1,4四分，四分位数]
conditional.quantile(frcst, obs, bins, thrs, main = "Sample Conditional Quantile Plot")
#### Or plots a ``cont.cont'' class object.[＃＃＃或绘制“cont.cont”类的对象。]
obs<- rnorm(100)
pred<- rnorm(100)
baseline <- rnorm(100, sd = 0.5)
A<- verify(obs, pred, baseline = baseline, frcst.type = "cont", obs.type = "cont")
plot(A)
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 2012-10-1 15:20:54
