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R语言 secr包 housemouse()函数中文帮助文档(中英文对照)

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发表于 2012-9-29 23:58:24 | 显示全部楼层 |阅读模式
housemouse(secr)
housemouse()所属R语言包:secr

                                         House mouse live trapping data  
                                         家鼠生活捕获的数据

                                         译者:生物统计家园网 机器人LoveR

描述----------Description----------

Data of H. N. Coulombe from live trapping of feral house mice (Mus musculus) in a salt marsh, California, USA.
数据HN Coulombe在美国加利福尼亚州的盐沼,从现场捕捉的野生小家鼠(小家鼠)。


用法----------Usage----------


data(housemouse)



Details

详细信息----------Details----------

H. N. Coulombe conducted a live-trapping study on an outbreak of feral house mice in a salt marsh in mid-December 1962 at Ballana Creek, Los Angeles County, California. A square 10 x 10 grid was used with 100 Sherman traps spaced 3 m apart. Trapping was done twice daily, morning and evening, for 5 days.
HN,Coulombe进行了现场捕获的研究小河Ballana,洛杉矶县,加利福尼亚州在1962年12月中旬在盐沼的野生小家鼠的一次爆发。一个10×10格方与100谢尔曼陷阱的间隔3米。诱捕,每日两次,早上和晚上,连续5天。

The dataset was described by Otis et al. (1978) and distributed with their CAPTURE software (now available from http://http://www.mbr-pwrc.usgs.gov/software.html). Otis et al. (1978 p. 62, 68) cite Coulombe's unpublished 1965 master's thesis from the University of California, Los Angeles, California.
奥的斯等人所描述的数据集。 (1978年)和分发他们的捕获的软件(现在可以从http://http://www.mbr-pwrc.usgs.gov/software.html,)。奥的斯等人。 (1978年第62页,68页)引用Coulombe的未公布的1965年硕士论文从美国加州大学洛杉矶分校,加利福尼亚州。

The data are provided as a single-session capthist object. There are two individual covariates: sex (factor levels "f", "m") and age class (factor levels "j", "sa", "a"). The sex of two animals is not available (NA); it is necessary to drop these records for analyses using "sex".
中所提供的数据作为一个单一的会话capthist对象。有两个独立的协变量:性别(因子水平F,M)和年龄结构(因子水平J,山,一)。两种动物的性别是不可用(NA),它是必要删除这些记录进行分析,用性。

The datasets were originally in the CAPTURE "xy complete" format which for each detection gives the "column" and "row" numbers of the trap (e.g. " 9 5" for a capture in the trap at position (x=9, y=5) on the grid). Trap identifiers have been recoded as strings with no spaces by inserting zeros (e.g. "0905" in this example).
最初的数据集在捕捉“XY完整的格式,为每个检测给人的列和行的数字陷阱(例如,”9“的陷阱中捕获位置(X = 9时,y = 5)在网格上)。陷阱标识符已经被重新编码为不带空格的字符串由的插入零(在这个例子中,例如0905)。

Sherman traps are designed to capture one animal at a time, but the data include 30 double captures and one occasion when there were 4 individuals in a trap at one time. The true detector type therefore falls between "single" and "multi". Detector type is set to "multi" in the distributed data objects.
谢尔曼被设计的陷阱捕捉动物的时间,但数据包括30个双捕获和一次有4个人在陷阱里的一次。因此,真正的探测器类型属于单和多之间。检测器的类型被设置为“多”,在分布式数据对象。

Otis et al. (1978) report various analyses including a closure test on the full data, and model selection and density estimation on data from the mornings only. We include several secr models fitted to the "morning" data (morning.0, morning.b etc.). Of these, a model including individual heterogeneity in both g0 and sigma has the lowest AIC.
奥的斯等人。 (1978)报告的分析,包括封闭测试的完整的数据和模型的选择和密度估计的数据只在上午。我们安装“今天上午的数据(morning.0,morning.b等)包括的几个秘书服务模型。在这些中,包括个别异质性g0和西格玛模型具有最低AIC。


源----------Source----------

File "examples" distributed with program CAPTURE.
文件的例子的分布式程序捕捉。


参考文献----------References----------

Statistical inference from capture data on closed animal populations. Wildlife Monographs 62, 1–135.

实例----------Examples----------



plot(housemouse, title = paste("Coulombe (1965), Mus musculus,",
    "California salt marsh"), border = 5, rad = 0.5,
    gridlines = FALSE)

morning <- subset(housemouse, occ = c(1,3,5,7,9))
summary(morning)

## drop 2 unknown-sex mice[#下降2未知性别的小鼠]
known.sex <- subset(housemouse, !is.na(covariates(housemouse)$sex))

## reveal multiple captures[#显示多个捕获]
table(trap(housemouse), occasion(housemouse))

AIC(morning.0, morning.b, morning.t, morning.h2, morning.0h2, morning.h2h2)

## assess need to distinguish morning and afternoon samples[#评估需要区分上午和下午的样本]
## Not run: [#不运行:]
housemouse.0 <- secr.fit (housemouse, buffer = 20)
housemouse.ampm <- secr.fit (housemouse, model = g0~tcov, buffer = 20,
    timecov = c(0,1,0,1,0,1,0,1,0,1))
AIC(housemouse.0, housemouse.ampm)

## 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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