edwards.eberhardt(RMark)
edwards.eberhardt()所属R语言包：RMark
Rabbit capture-recapture data
兔捕获 - 再捕获数据
译者：生物统计家园网 机器人LoveR
描述----------Description----------
A capture-recapture data set on rabbits derived from Edwards and Eberhardt (1967) that accompanies MARK as an example analysis using the closed population models.
一个捕获 - 再捕获的数据集对兔子来自爱德华兹和埃贝哈特（1967年），伴随着MARK采用封闭式的人口模型为例进行分析。
格式----------Format----------
A data frame with 76 observations on the following variable.
一个数据框与76观察下面的变量。
ch a character vector
CH字符向量
Details
详细信息----------Details----------
This data set is used in MARK to illustrate the various closed population models including "Closed", "HetClosed", "FullHet","Huggins","HugHet", and "FullHugHet". The first 3 include N in the likelihood whereas the last 3 are based on the Huggins approach which does not use N in the likelihood. The Het... and FullHet... models are based on the Pledger mixture model approach. Some of the examples demonstrate the use of the share argument in the model.parameters list for parameter p which allows sharing common values for p and c.
此数据集是用在将MARK示出的各种封闭人口的模型，包括“关闭”，“HetClosed”中，“FullHet”，“哈金斯”，“HugHet”，和“FullHugHet”。的前三包括N合的可能性，而在过去的3基于Huggins的方法，不使用的可能性中的N。 HET ... FullHet ...模型是基于质混合模型的方法。的例子演示了如何使用share参数在model.parameters列表中的参数pp和c可以分享共同的价值观。
源----------Source----------
Edwards, W.R. and L.L. Eberhardt 1967. Estimating cottontail abundance from live trapping data. J. Wildl. Manage. 31:87-96.
爱德华兹，W.R.和L.L.埃贝哈特1967年。从现场捕获数据估算棉尾丰富。 J. Wildl。管理。 31:87-96。
实例----------Examples----------
#[]
# get data[获取数据]
#[]
data(edwards.eberhardt)
#[]
# create function that defines and runs the analyses as defined in[创建函数定义和运行中所定义的分析]
# MARK example dbf file[标记示例dbf文件]
#[]
run.edwards.eberhardt=function()
{
#[]
# Define parameter models[定义参数模型]
#[]
pdotshared=list(formula=~1,share=TRUE)
ptimeshared=list(formula=~time,share=TRUE)
ptime.c=list(formula=~time+c,share=TRUE)
ptimemixtureshared=list(formula=~time+mixture,share=TRUE)
pmixture=list(formula=~mixture)
#[]
# Run assortment of models[运行模型的分类]
#[]
#[]
# Capture Closed models[捕捉封闭模型]
#[]
# constant p=c[常数p = C]
ee.closed.m0=mark(edwards.eberhardt,model="Closed",
model.parameters=list(p=pdotshared))
# constant p and constant c but different[常数p和常数c，但不同的]
ee.closed.m0c=mark(edwards.eberhardt,model="Closed")
# time varying p=c[随时间变化的P = C]
ee.closed.mt=mark(edwards.eberhardt,model="Closed",
model.parameters=list(p=ptimeshared))
#[]
# Closed heterogeneity models[关闭异质性模型]
#[]
# 2 mixtures Mh2[2混合物MH2]
ee.closed.Mh2=mark(edwards.eberhardt,model="HetClosed",
model.parameters=list(p=pmixture))
# Closed Mth2 - p different for time; mixture additive[关闭MTH2 - P不同的时间，水煤浆添加剂]
ee.closed.Mth2.additive=mark(edwards.eberhardt,model="FullHet",
model.parameters=list(p=ptimemixtureshared),adjust=TRUE)
#[]
# Huggins models[哈金斯模型]
#[]
# p=c constant over time[P = C随时间变化]
ee.huggins.m0=mark(edwards.eberhardt,model="Huggins",
model.parameters=list(p=pdotshared))
# p constant c constant but different; this is default model for Huggins[P常数的恒定，但不同的，这是默认模式哈金斯]
ee.huggins.m0.c=mark(edwards.eberhardt,model="Huggins")
# Huggins Mt[哈金斯山]
ee.huggins.Mt=mark(edwards.eberhardt,model="Huggins",
model.parameters=list(p=ptimeshared),adjust=TRUE)
#[]
# Huggins heterogeneity models[哈金斯异质性模型]
#[]
# Mh2 - p different for mixture[不同的混合MH2 - P]
ee.huggins.Mh2=mark(edwards.eberhardt,model="HugHet",
model.parameters=list(p=pmixture))
# Huggins Mth2 - p different for time; mixture additive[哈金斯MTH2 - P不同的时间，水煤浆添加剂]
ee.huggins.Mth2.additive=mark(edwards.eberhardt,model="HugFullHet",
model.parameters=list(p=ptimemixtureshared),adjust=TRUE)
#[]
# Return model table and list of models[回归模型的表格和列表的车型]
#[]
return(collect.models() )
}
#[]
# fit models in mark by calling function created above[的适配机型在标记通过调用函数上面创建的]
#[]
ee.results=run.edwards.eberhardt()
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。
|
发表于 2012-9-26 23:40:53
