suggest.buffer(secr)
suggest.buffer()所属R语言包：secr
Mask Buffer Width
模板缓冲区宽度
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Determines a suitable buffer width for an integration mask. The "buffer" in question defines a concave polygon around a detector array constructed using make.mask with type = "trapbuffer". The method relies on an approximation to the bias of maximum likelihood density estimates (Efford and Marques unpubl).
确定适当的缓冲液的积分宽度为掩模。问题定义的“缓冲”凹多边形周围的探测器阵列建造make.mask与type = "trapbuffer"。该方法依赖于一个近似的最大似然密度的估计（Efford和Marques未发表）的偏见。
用法----------Usage----------
suggest.buffer(object, detectfn = NULL, detectpar = NULL,
noccasions = NULL, RBtarget = 0.001, interval = NULL, ...)
bias.D (buffer, traps, detectfn, detectpar, noccasions,
control = NULL)
参数----------Arguments----------
参数：object
"secr", "traps" or "capthist" object
“秘书服务”，“陷阱”或“capthist”的对象
参数：detectfn
integer code or character string for shape of detection function 0 = halfnormal etc. – see detectfn
的整数代码或字符串检测功能0 = halfnormal等形状 - detectfn
参数：detectpar
list of values for named parameters of detection function – see detectpar
列表值命名参数的检测功能 - detectpar
参数：noccasions
number of sampling occasions
样本的数量
参数：RBtarget
numeric target for relative bias of density estimate
数字目标的密度估计的相对偏差
参数：interval
a vector containing the end-points of the interval to be searched
一个向量，包含的结束点的时间间隔要搜索
参数：...
other argument(s) passed to bias.D
其他参数（S）传递给bias.D
参数：buffer
vector of buffer widths
矢量缓冲区的宽度
参数：traps
"traps" object
“陷阱”对象
参数：control
list of mostly obscure numerical settings (see Details)
大多是模糊的数值设置列表（见详情）
Details
详细信息----------Details----------
The basic input style of suggest.buffer uses a "traps" object and a detection model specified by "detectpar", "detectfn" and "noccasions", plus a target relative bias (RB). A numerical search is conducted for the buffer width that is predicted to deliver the requested RB. If interval is omitted it defaults to (1, 100S) where S is the spatial scale of the detection function (usually detectpar$sigma). An error is reported if the required buffer width is not within interval. This often happens with heavy-tailed detection functions (e.g., hazard-rate): choose another function, a larger RBtarget or a wider interval.
基本输入风格suggest.buffer使用一个陷阱detectpar，detectfn和noccasions，加上目标相对偏差（RB）所指定的对象和一个检测模型。预测来提供所请求的RB为缓冲区的宽度的数值进行搜索。如果interval被省略时，默认为（1，100S），其中，S是空间尺度的检测功能（通常是detectpar$sigma）。如果所需的缓冲区宽度不属于interval会报告一个错误。这种情况经常发生重尾检测功能（例如，危险率）：选择另外一个功能，一个更大的RBtarget或更广泛的interval。
Convenient alternative input styles are –
方便的替代性输入方式是 -
secr object containing a fitted model. Values of "traps", "detectpar", "detectfn" and "noccasions" are extracted from object and any values supplied for these arguments are ignored.
secr物件，其中包含一个合适的模型。提取object的陷阱，detectpar“，”detectfn“和”noccasions“的值，并提供这些参数的值将被忽略。
capthist object containing raw data. If detectpar is not supplied then autoini is used to get "quick and dirty" values of g0 and sigma for a halfnormal detection function. noccasions is ignored. autoini tends to underestimate sigma, and the resulting buffer also tends to be too small.
capthist物件，其中包含原始数据。如果detectpar没有提供，则autoini使用“快速和肮脏的值g0和sigma为一个halfnormal的检测功能。 noccasions被忽略。 autoini低估sigma的倾向，和所得到的缓冲液也往往是太小。
bias.D is called internally by suggest.buffer.
bias.D内部被称为suggest.buffer。
The package gpclib may be used for more accurate estimates of the length of buffer contours (this does not appear to be critical). Some components of control are specific to this part of the algorithm (ntheta, ninterp, maxinterp).
包gpclib可用于更准确地估计缓冲轮廓的长度（不出现是至关重要的）。某些组件control是针对这部分的算法（ntheta，ninterp，maxinterp）。
值----------Value----------
suggest.buffer returns a scalar value for the suggested buffer width in metres, or a vector of such values in the case of a multi-session object.
suggest.buffer返回标量值的所建议的缓冲以米为单位的宽度，或者在一个多会话object的情况下的这样的值的矢量。
bias.D returns a dataframe with columns buffer and RB.D (approximate bias of density estimate using finite buffer width, relative to estimate with infinite buffer).
bias.D返回一个数据框的列buffer和RB.D（近似密度估计的偏差，利用有限的缓冲区宽度，相对估计与无限缓冲）。
注意----------Note----------
The algorithm in bias.D uses one-dimensional numerical integration of a polar approximation to site-specific detection probability. By default, and when gpclib is not available, this uses a further 3-part linear approximation for the length of contours of distance-to-nearest-detector (r) as a function of r.
该算法在bias.D使用一维数值积分的极性近似位点特异性的检测概率。默认情况下，当gpclib是不可用的，这会使用另外3个部分组成的线性近似的长度轮廓的距离，到最近的检测（r）<X的函数>。
The approximation seems to work well for a compact detector array, but it should not be taken as an estimate of the bias for any other purpose: do not report RB.D as "the relative bias of the density estimate". RB.D addresses only the effect of using a finite buffer. The effect of buffer width on final estimates should be checked with mask.check.
这种近似似乎运作良好的紧凑型探测器阵列，但它不应该被用于任何其他用途的估计的偏差：不报告RB.D“的密度估计的相对偏差”。 RB.D解决的影响，利用有限的缓冲区。与mask.check的影响，最终估计应检查的缓冲区宽度。
The default buffer type in make.mask, and hence in secr.fit, is "traprect", not "trapbuffer", but a buffer width that is adequate for "trapbuffer" is always adequate for "traprect".
默认的缓冲区类型make.mask，并因此在secr.fit，是traprect，而不是告警缓冲区“，但”告警缓冲区是足够的缓冲区宽度始终是足够的traprect“。
control contains various settings of little interest to the user.
control包含各种设置的用户兴趣不大。
The potential components of control are –
control的潜在 -
method = 1 code for method of modelling p.(X) as a
method = 1 代码（X）作为一个为方法建模p。
bfactor = 20 q(r) vs p.(X) calibration
bfactor = 20 Q（R）与第（X）校准
masksample = 1000 maximum number of points sampled from
masksample = 1000 最大数量的点采样，
spline.df = 10 effective degrees of freedom for
spline.df = 10 有效的自由度
use.gpclib = FALSE logical to use gpclib if
use.gpclib = FALSE 合理使用gpclib如果
ntheta = 60 integer value for smoothness of contours
ntheta = 60 整数值平滑的轮廓
ninterp = 5 number of points to interpolate between trapspacing/2 and trapspacing/2 ^0.5 on the contour-length vs buffer
ninterp = 5 数量的点之间进行内插/ 2 trapspacing和trapspacing / 2 ^ 0.5上的轮廓线的长度与缓冲液
参见----------See Also----------
mask, make.mask, mask.check, esa.plot
mask，make.mask，mask.check，esa.plot
实例----------Examples----------
## Not run: [＃不运行：]
temptraps <- make.grid()
detpar <- list(g0 = 0.2, sigma = 25)
suggest.buffer(temptraps, "halfnormal", detpar, 5)
RB <- bias.D(50:150, temptraps, "halfnormal", detpar, 5)
plot(RB)
detpar <- list(g0 = 0.2, sigma = 25, z=5)
RB <- bias.D(50:150, temptraps, "hazard rate", detpar, 5)
lines(RB)
## compare to esa plot[＃欧空局图比较]
esa.plot (temptraps, max.buffer = 150, spacing = 4, detectfn = 0,
detectpar = detpar, noccasions = 5, as.density = F)
## End(Not run)[＃（不执行）]
## compare detection histories and fitted model as [比较检测的历史和拟合模型]
suggest.buffer(ovenCH)
suggest.buffer(ovenbird.model.1)
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 2012-9-30 00:06:19
