detectfn(secr)
detectfn()所属R语言包：secr
Detection Functions
检测功能
译者：生物统计家园网 机器人LoveR
描述----------Description----------
A detection function relates the probability of detection to the distance of a detector from a point. The reference point is usually thought of as an animal's home-range centre. In secr only simple 2- or 3-parameter functions are used. Each type of function is identified by a numeric code (see below). In most cases the name may also be used (as a quoted string).
A检测功能涉及从一个点的距离的检测器检测到的概率。参考点通常被认为是动物的家庭范围的中心。在secr只有简单的2 - 或3 - 参数的功能被使用。每种类型的功能来识别由数字代码（见下文）。在大多数情况下的名称也可以使用（作为一个引用的字符串）。
Some functions such as (4) uniform are defined only for simulation as the pose problems for maximum likelihood.
仅被定义用于仿真的某些功能的条件，如（4）均匀，作为最大似然的姿势的问题。
For function (7), "F" is the standard normal distribution function and μ and s are the mean and standard deviation on the log scale of a latent variable representing a threshold of detection distance. See Note for the relationship to the fitted parameters sigma and z.
（7）对于函数，F是标准正态分布函数和μ和s的log规模的潜变量的阈值探测距离的平均值和标准偏差。见注拟合参数的标准差和Z的关系。
For function (8), "G" is the cumulative distribution function of the gamma distribution with shape parameter k ( = z) and scale parameter θ ( = sigma/z). See R's pgamma.
对于功能（8），G是伽玛分布的累积分布函数的形状参数k（=z）和尺度参数θ（sigma/z）。 R的pgamma。
For functions (9), (10) and (11), "F" is the standard normal distribution function and "c" is an arbitrary signal threshold. The two parameters of (9) are functions of the parameters of (10) and (11): b0 = (beta0--c)/sdS and b1 = beta1/s (see Efford et al. 2009).
对于功能（9），（10）和（11），“F”是标准正态分布函数和c是一个任意的信号阈值。的两个参数的函数的参数（10）和（11）：b0 = (beta0--c)/sdS和b1 = beta1/s（见Efford等2009）（9）。
Function (11) includes an additional "hard-wired" term for sound attenuation due to spherical spreading. Detection probability at distances less than 1 m is given by g(d) = 1 -- F{(c -- beta0) / sdS }
功能（11）包括一个附加的“硬接线”的术语，由于球面扩散的声音衰减。在距离小于1米的检测概率是由 g(d) = 1 -- F{(c -- beta0) / sdS } 的
The hazard-rate detection function was described by Hayes and Buckland (1983). The compound halfnormal detection function follows Efford and Dawson (2009). The signal strength and binary signal strength functions are from Efford et al. (2009).
海耶斯和巴克兰（1983）所描述的危险率检测功能。复合halfnormal检测的功能如下Efford和道森（2009）。的信号强度和二进制信号强度功能从Efford等。 （2009年）。
注意----------Note----------
The parameters of function (7) are potentially confusing. The fitted parameters describe a latent threshold variable on the natural scale: sigma (mean) = exp(μ + s^2/2) and z (standard deviation) = sqrt(exp(s^2+2*μ)*(exp(s^2)--1))). As with other detection functions, sigma is a spatial scale parameter, although in this case it corresponds to the mean of the threshold variable; the standard deviation of the threshold variable (z) determines the shape
功能（7）的参数中可能造成混乱。拟合参数描述了一个潜在的阈值变量的自然规模：SIGMA（平均）=exp(μ + s^2/2)和z（标准差）=sqrt(exp(s^2+2*μ)*(exp(s^2)--1)))。至于与其他的检测功能，σ是一个空间尺度参数，虽然在这种情况下，它对应的阈值变量的平均值的阈值变量的标准偏差（z）的确定的形状
参考文献----------References----------
heterogeneity on population size estimates from point counts. Auk 126, 100–111.
density estimated from locations of individuals on a passive detector array. Ecology 90, 2676–2682.
line-transect method. Biometrics 39, 29–42.
参见----------See Also----------
detectfnplot, secr detection models
detectfnplot，secr detection models
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。
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发表于 2012-9-29 23:56:34
