estSigmaR(scape)
estSigmaR()所属R语言包：scape
Estimate Recruitment Sigma
估计招聘西格玛
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Estimate sigma R (recruitment variability), based on the empirical standard deviation of recruitment deviates in log space.
估计标准差中R（招聘变异），基于经验的标准差招聘偏离的log空间。
用法----------Usage----------
estSigmaR(model, digits=2)
参数----------Arguments----------
参数：model
fitted scape model containing element Dev.
装scape模型包含的元素Dev。
参数：digits
number of decimal places to use when rounding, or NULL to suppress rounding.
使用时，四舍五入，或NULL抑制四舍五入的小数位数。
值----------Value----------
Vector of two numbers, estimating recruitment variability based on (1) the estimated age composition in the first year, and (2) subsequent annual recruitment.
向量的两个数字估计招聘变异（1）估计年龄结构的第一年，和（2）随后的年度招聘的基础上。
注意----------Note----------
This function uses the empirical standard deviation to estimate sigma R, which may be appropriate as likelihood penalty (or Bayesian prior distribution) for recruitment deviates from the stock-recruitment curve. The smaller the estimated recruitment deviates, the smaller the estimated sigma R.
该函数使用经验的标准偏差估计西格玛R，这可能是适当的，因为招聘偏离从股票的招聘曲线的可能性罚款（或贝叶斯的先验分布）。估计招募偏离越小，较小的估计西格玛R.
estSigmaR can be used iteratively, along with estN and estSigmaI to assign likelihood weights that are indicated by the model fit to the data. Sigmas and sample sizes are then adjusted between model runs, until they converge. The iterate function facilitates this procedure.
estSigmaR可以反复使用，随着estN和estSigmaI分配的可能性表示的权重，通过模型拟合的数据。 Sigma的样本量之间调节模式运行，直到收敛。 iterate功能简化此过程。
If ss is the sum of squared recruitment deviates in log space and n is the number of estimated recruitment deviates, then the estimated sigma R is:
如果ss的总和的平方招聘会偏离log空间，并n是数的估计招聘偏离，那么估计西格玛R是：
The denominator is neither n-1 nor n-p, since ss is based on deviates from zero and not the mean, and the deviates do not converge to zero as the number of model parameters increases.
分母是既不n-1也不n-p，因为ss从零偏离，而不是平均值的基础上，和偏离不收敛到零作为增加的模型的参数的数目。
参见----------See Also----------
getN, getSigmaI, getSigmaR, estN, estSigmaI, and estSigmaR extract and estimate sample sizes and sigmas.
getN，getSigmaI，getSigmaR，estN，estSigmaI和estSigmaR提取和估计的样本量和逐步改善。
iterate combines all the get* and est* functions in one call.
iterate将所有的get*和est*在一个呼叫的功能。
plotN and plotB(..., what="s") show what is behind the sigma R estimation.
plotN和plotB(..., what="s")的sigmaŕ估计的背后是什么。
scape-package gives an overview of the package.
scape-package给出了一个概述的包。
实例----------Examples----------
getSigmaR(x.cod) # sigmaR used in assessment 0.5 and 1.0[西格玛用于评估0.5和1.0]
estSigmaR(x.cod) # model estimates imply 0.20 and 0.52[模型的估计数意味着0.20和0.52]
getSigmaR(x.ling) # 0.6, deterministic age distribution in first year[0.6，确定的年龄分布在第一年]
estSigmaR(x.ling) # model estimates imply 0.36[模型的估计数意味着0.36]
getSigmaR(x.sbw)
estSigmaR(x.sbw) # large deviates in first year[在第一年的大背离]
plotN(x.sbw) # enormous plus group and 1991 cohort[巨大的加群和1991年的队列]
# x.oreo assessment had deterministic recruitment, so no deviates[x.oreo评估确定的招聘，所以没有偏离]
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 2012-9-29 22:42:19
