represampling.bootstrap(sperrorest)
represampling.bootstrap()所属R语言包:sperrorest
Non-spatial bootstrap resampling
非空间引导重采样
译者:生物统计家园网 机器人LoveR
描述----------Description----------
represampling.bootstrap draws a bootstrap random sample (with replacement) from data.
represampling.bootstrap绘制一个自举随机样本(更换)data。
用法----------Usage----------
represampling.bootstrap(data, coords = c("x", "y"),
nboot = nrow(data), repetition = 1, seed1 = NULL,
oob = FALSE)
参数----------Arguments----------
参数:coords
vector of length 2 defining the variables in data that contain the x and y coordinates of sample locations
向量,长度为2data包含的x和y坐标的样本的位置定义的变量在
参数:nboot
Size of bootstrap sample
引导样品的大小
参数:oob
logical (default FALSE): if TRUE, use the out-of-bag sample as the test sample; if FALSE, draw a second bootstrap sample of size nboot independently to obtain a test sample
逻辑(默认FALSE):如果TRUE,使用袋样品作为测试样本,如果FALSE,画第二个引导的大小nboot独立样本获得试验样品
参数:data
data.frame containing at least the columns specified by coords
data.frame的至少包含列指定的coords
参数:repetition
numeric vector: cross-validation repetitions to be generated. Note that this is not the number of repetitions, but the indices of these repetitions. E.g., use repetition=c(1:100) to obtain (the 'first') 100 repetitions, and repetition=c(101:200) to obtain a different set of 100 repetitions.
数字向量:交叉验证的重复产生。注意,这是不重复的次数,但这些重复的指数。例如,使用repetition=c(1:100)(“第一个”)取得100个重复,和repetition=c(101:200)获得一组不同的重复100次。
参数:seed1
seed1+i is the random seed that will be used by set.seed in repetition i (i in repetition) to initialize the random number generator before sampling from the data set.
seed1+i是随机的种子,将用于set.seed重复i(irepetition)采样前的数据初始化随机数生成器设置。
值----------Value----------
A represampling object. This is a (named) list containing length(repetition) resampling objects. Each of these contains only one list with indices of training and test samples. Indices are row indices for data.
Arepresampling对象。这是一个(命名)的列表,其中包含length(repetition)resampling的对象。这些指数train荷兰国际集团和test样品只包含一个列表。指数指数data行。
实例----------Examples----------
data(ecuador)
# only 10 bootstrap repetitions, normally use >=100:[只有10个引导的重复,一般使用> = 100:]
parti = represampling.bootstrap(ecuador, repetition = 10)
plot(parti, ecuador) # careful: overplotting occurs[注意:overplotting发生]
# because some samples are included in both the training and[因为一些样品都包含在两个训练和]
# the test sample (possibly even multiple times)[测试样品(甚至可能多次)]
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。
注:
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