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R语言 unmarked包 occu()函数中文帮助文档(中英文对照)

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发表于 2012-10-1 13:25:22 | 显示全部楼层 |阅读模式
occu(unmarked)
occu()所属R语言包:unmarked

                                        Fit the MacKenzie et al. (2002) Occupancy Model
                                         适合Mackenzie等人。 (2002)出租模型

                                         译者:生物统计家园网 机器人LoveR

描述----------Description----------

This function fits the single season occupancy model of MacKenzie et al (2002).
此功能适合的单季占用的麦肯齐等人(2002)的模型。


用法----------Usage----------





参数----------Arguments----------

参数:formula
Double right-hand side formula describing covariates of detection and occupancy in that order.
双人右手边式描述的检测和占用协变量的顺序。


参数:data
An unmarkedFrameOccu object
unmarkedFrameOccu对象


参数:knownOcc
Vector of sites that are known to be occupied. These should be supplied as row numbers of the y matrix, eg, c(3,8) if sites 3 and 8 were known to be occupied a priori.
被占用,被称为向量的网站。这些行号的Y矩阵,例如,C(3,8),应提供被称为是占据了如果网站3和8。


参数:starts
Vector of parameter starting values.
向量参数的初始值。


参数:method
Optimization method used by optim.
优化所使用的方法optim。


参数:se
Logical specifying whether or not to compute standard errors.
逻辑指定是否计算标准误差。


参数:engine
Either "C" or "R" to use fast C++ code or native R code during the optimization.
无论是“C”或“R”使用快速的C + +代码或本机在优化过程中的R代码。


参数:...
Additional arguments to optim, such as lower and upper bounds
其他参数OPTIM,如上限和下限


Details

详细信息----------Details----------

See unmarkedFrame and unmarkedFrameOccu for a description of how to supply data to the data argument.
见unmarkedFrame和unmarkedFrameOccu如何提供数据data参数的描述。

occu fits the standard occupancy model based on zero-inflated binomial models (MacKenzie et al. 2006, Royle and Dorazio 2008).  The occupancy state process (z_i) of site i is modeled as
occu符合标准的占用模型的基础上的零膨胀二项式模型(Mackenzie等人,2006年,罗伊尔和Dorazio 2008)。占用状态的过程(z_i)的网站i建模为

The observation process is modeled as
观察过程建模

Covariates of psi_i and p_ij are modeled using the logit link according to the formula argument.  The formula is a double right-hand sided formula like ~ detform ~ occform where detform is a formula for the detection process and occform is a formula for the partially observed occupancy state.  See formula for details on constructing model formulae
协变量的psi_i和p_ij根据formula参数logit的关联建模。其计算公式为一个双右手侧式~ detform ~ occformdetform是在检测过程中的公式和occform是一个公式的部分可观测的占用状态。为上构建模型公式的详细信息,请参阅公式


值----------Value----------

unmarkedFitOccu object describing the model fit.
描述模型拟合unmarkedFitOccu对象。


(作者)----------Author(s)----------


Ian Fiske



参考文献----------References----------

J. Andrew Royle, and C. A. Langtimm. 2002. Estimating Site Occupancy Rates When Detection Probabilities Are Less Than One. Ecology 83: 2248-2255.
Amsterdam: Academic Press.
in Ecology. Academic Press.

参见----------See Also----------

unmarked, unmarkedFrameOccu,
unmarked,unmarkedFrameOccu,


实例----------Examples----------



data(frogs)
pferUMF <- unmarkedFrameOccu(pfer.bin)
plot(pferUMF, panels=4)
# add some fake covariates for illustration[添加一些假的协变量说明]
siteCovs(pferUMF) <- data.frame(sitevar1 = rnorm(numSites(pferUMF)))

# observation covariates are in site-major, observation-minor order[观察协变量是在主要站点,观察未成年人为了]
obsCovs(pferUMF) <- data.frame(obsvar1 = rnorm(numSites(pferUMF) * obsNum(pferUMF)))

(fm <- occu(~ obsvar1 ~ 1, pferUMF))

confint(fm, type='det', method = 'normal')
confint(fm, type='det', method = 'profile')

# estimate detection effect at obsvars=0.5[估计检测效果obsvars = 0.5]
(lc <- linearComb(fm['det'],c(1,0.5)))

# transform this to probability (0 to 1) scale and get confidence limits[把这种概率(0~1)的规模,并得到置信限]
(btlc <- backTransform(lc))
confint(btlc, level = 0.9)

# Empirical Bayes estimates of proportion of sites occupied with 95% CI[经验贝叶斯估计网站的比例占据95%CI]
# No uncertainty because p is so high![的不确定性,因为p是如此之高!]
re <- ranef(fm)
c("PAO"=sum(bup(re, stat="mode")), colSums(confint(re)))


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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