circular(secr)
circular()所属R语言包：secr
Circular Probability
通函概率
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Functions to answer the question "what radius is expected to include proportion p of points from a circular bivariate distribution corresponding to a given detection function", and the reverse. These functions may be used to relate the scale parameter(s) of a detection function (e.g., σ) to home-range area (specifically, the area within an activity contour for the corresponding simple home-range model) (see Note).
功能来回答这个问题：“什么半径预计将包括圆形对应一个给定的检测功能”的二元分布比例p点，反向。这些功能可以用来与尺度参数（S）的检测功能（例如，σ）家庭范围内的区域（特别是区域内相应的简单的家庭范围模型的活动轮廓）（见注）。
用法----------Usage----------
circular.r (p = 0.95, detectfn = 0, sigma = 1, detectpar = NULL)
circular.p (r = 1, detectfn = 0, sigma = 1, detectpar = NULL)
参数----------Arguments----------
参数：p
vector of probability levels for which radius is required
矢量的概率水平半径需要
参数：r
vector of radii for which probability level is required
矢量半径的概率水平是必需的
参数：detectfn
integer code or character string for shape of detection function 0 = halfnormal, 1 = hazard rate etc. – see detectfn
形状的检测功能0 = halfnormal，1 =风险率等的的整数代码或字符的字符串 - detectfn
参数：sigma
spatial scale parameter of detection function
空间尺度参数的检测功能
参数：detectpar
named list of detection function parameters
指定检测功能参数列表
Details
详细信息----------Details----------
circular.r is the quantile function of the specified circular bivariate distribution (analogous to qnorm, for example). The quantity calculated by circular.r is sometimes called 'circular error probable' (see Note).
circular.r是位数的指定的圆形二元分布函数（类似于qnorm，例如）。数量计算的circular.r有时也被称为“圆概率误差（见注）。
For detection functions with two parameters (intercept and scale) it is enough to provide sigma. Otherwise, detectpar should be a named list including parameter values for the requested detection function (g0 may be omitted, and order does not matter).
对于带有两个参数的检测功能（拦截和规模），它是足以提供sigma。否则，detectpar应该是一个名为list的参数值所要求的检测功能（G0可以省略，顺序并不重要）。
值----------Value----------
Vector of values for the required radii or probabilities.
为所需的半径或概率的值的向量。
注意----------Note----------
The term "circular error probable" has a military origin. It is commonly used for GPS accuracy with the default probability level set to 0.5 (i.e. half of locations are further than CEP from the true location). A circular bivariate normal distriubution is commonly assumed for the circular error probable; this is equivalent to setting detectfn = "halfnormal".
“圆概率误差有一个军人出身的。它通常用于GPS的精度与默认设置为0.5（即一半的位置从真正的位置进一步的比CEP）的概率水平。一个圆形的二元的正常distriubution通常假定为圆概率误差;这相当于设置detectfn = "halfnormal"。
Closed-form expressions are used for the normal and uniform cases; in the bivariate normal case, the relationship is r = (-2*log(1-p))^0.5 * sigma. Otherwise, the probability is computed numerically by integrating the radial distribution. Numerical integration is not foolproof, so check suspicious or extreme values.
封闭形式的表达式是用于正常的，统一的情况下，在的二元正常情况下，这种关系是r = (-2*log(1-p))^0.5 * sigma。否则，概率的计算数值通过整合的径向分布。数值积分也不是万无一失的，所以检查可疑或极端值。
When circular.r is used with the default sigma = 1, the result may be interpreted as the factor by which sigma needs to be inflated to include the desired proportion of activity (e.g., 2.45 sigma for 95% of points from a circular bivariate normal distribution).
当circular.r使用的默认sigma = 1，其结果可能被解释为西格玛需要的因子，包括活动所需的比例（例如，2.45标准差为95％的点被夸大圆形二元正态分布）。
参考文献----------References----------
density of small mammals. Public Health Monograph No. 55. United States Government Printing Office.
参见----------See Also----------
detectfn, detectfnplot
detectfn，detectfnplot
实例----------Examples----------
## Calhoun and Casby (1958) p 3.[＃卡尔霍恩和Casby的（1958）第3页。]
## give p = 0.3940, 0.8645, 0.9888[＃给P = 0.3940，0.8645，0.9888。]
circular.p(1:3)
## halfnormal, hazard-rate and exponential[＃halfnormal，危险率和指数]
circular.r ()
circular.r (detectfn = 1, detectpar = list(sigma = 1, z = 4))
circular.r (detectfn = 2)
plot(seq(0, 5, 0.01), circular.p(r = seq(0, 5, 0.01)),
type = "l", xlab = "Radius (multiples of sigma)", ylab = "Probability")
lines(seq(0, 5, 0.01), circular.p(r = seq(0, 5, 0.01), detectfn = 2),
type = "l", col = "red")
lines(seq(0, 5, 0.01), circular.p(r = seq(0, 5, 0.01), detectfn = 1,
detectpar = list(sigma = 1,z = 4)), type = "l", col = "blue")
abline (h = 0.95, lty = 2)
legend (2.8, 0.3, legend = c("halfnormal","hazard-rate, z = 4", "exponential"),
col = c("black","blue","red"), lty = rep(1,3))
## in this example, a more interesting comparison would use[＃在这个例子中，将使用一个更有趣的比较]
## sigma = 0.58 for the exponential curve.[＃σ= 0.58的指数曲线。]
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 2012-9-29 23:55:00
