metropolis(tripEstimation)
metropolis()所属R语言包：tripEstimation
Metropolis-Hastings sampler for location estimation for archival and satellite tag
大都市黑斯廷斯取样档案和卫星标记的位置估计
译者：生物统计家园网 机器人LoveR
描述----------Description----------
These functions provide a direct implementation of the Metropolis-Hastings algorithm, for calculating marginal posterior (locations and full-track estimates) properties using Markov Chain Monte Carlo. The sampler is written completely in R, vectorized to be as fast as possible. The sampler can include likelihood functions for large data records (including light and water temperature), as well as mask functions for simpler rejection sources. Behavioural constraints are implemented using a red/black update, so that location estimates X and Z may be estimated in an efficient manner. The parameter estimates may be cached and later queried arbitrarily.
这些功能提供了一个直接执行的Metropolis-Hastings算法，计算后验边缘（位置和轨道的估计）特性，利用马尔可夫链蒙特卡罗。取样器完全用R，矢量化，以尽可能快。采样器可以包括大型数据记录（包括光与水的温度），以及为简单的排斥反应源的掩模函数的似然函数。实施行为约束使用红色/黑色的更新，使该位置估计X和Z可以以高效的方式估计。参数估计值可缓存后查询任意。
用法----------Usage----------
metropolis(model, iters = 1000, thin = 10, start.x = NULL, start.z = NULL)
metropolis0(model, iters = 1000, thin = 10, start.x = NULL, start.z =
NULL)
参数----------Arguments----------
参数：model
model for estimation, such as one created by solar.model
模型估计中，如创建的solar.model的
参数：iters
number of iterations to run
的迭代次数，运行
参数：thin
number of iterations to thin by
迭代次数薄了
参数：start.x
starting points for the primary locations
为主要位置的起点
参数：start.z
starting points for the intermediate locations (midpoints between the start.x points is a good first guess
出发点的中间位置（start.x点之间的中点，是一个很好的猜测
Details
详细信息----------Details----------
metropolis0 is a slightly different version of metropolis that enables an initialization step, required to find parameter estimates that are consistent with any masks used. It is difficult to make this step more elegant, and so we live with the two versions.
metropolis0是一个版本略有不同，metropolis，使一个初始化步骤，需要找到符合使用任何口罩的参数估计，。这是很难走这一步更优雅，所以我们住在一起的两个版本。
In terms of the estimates, X's have m records with n parameters, where m is the number of data records in time (twilights for archival tags, Argos estimates for satellite tags) and n is at least x-coordinate, y-coordinate and maybe k-attenuation for light. Z's have m-1 records with 2 parameters for 'x' and 'y' (which are usually Longitude and Latitude). These parameters may be increased or changed, they are tied only to the likelihood functions used, not the sampler itself. Also, coordinate transformations may be used inside the model and likelihood functions, in order to use an appropriate map projection. Solar calculations rely on lon/lat and so this step does slow down light level geo-location.
估计，X的有m的记录n参数，其中m是多条数据记录的时间（黄昏档案标签，雅高卫星标签的估计）和 n至少是x坐标，y坐标，也许K-衰减的光。 Z的有m-1的2个参数为x和Y（经度和纬度）的记录。可以增加或改变这些参数，它们并列仅对使用的似然函数，而不是采样本身。此外，坐标变换可用于内部的模型和似然函数，为了使用一个适当的图投影。依靠太阳能计算经度/纬度，所以这一步会慢下来光水平GEO位置。
值----------Value----------
A MCM Chain stored as a list containing <table summary="R valueblock"> <tr valign="top"><td>model </td> <td> The model object used by the sampler</td></tr> <tr valign="top"><td>x </td> <td> The last iters X-samples accepted, stored as an c(m, n, iters) array </td></tr> <tr valign="top"><td>z </td> <td> The last iters Z-samples accepted, stored as an c(m - 1, 2, iters)</td></tr> <tr valign="top"><td>last.x </td> <td> The last accepted X-sample, stored as a c(m, n) matrix</td></tr> <tr valign="top"><td>last.z </td> <td> The last accepted Z-sample, stored as a c(m, 2) matrix</td></tr> </table>
在MCM链存储为一个列表，其中包含<table summary="R valueblock"> <tr valign="top"> <TD> model </ TD> <TD>采样器所使用的模型对象</ TD > </ TR> <tr valign="top"> <TD>x </ TD> <TD>最后iters接受的X-样本作为c(m, n, iters)阵列，存储< / TD> </ TR> <tr valign="top"> <TD> z </ TD> <TD>最后itersZ-的样本接受，存储为一个c(m - 1, 2, iters) </ TD> </ TR> <tr valign="top"> <TD>last.x </ TD> <TD>最后接受了X-样本，存储为一个c(m, n)矩阵</ TD > </ TR> <tr valign="top"> <TD> last.z </ TD> <td>在上次接受Z-样品，存储为一个c(m, 2)矩阵</ TD> </ TR> </ TABLE>
（作者）----------Author(s)----------
Michael D. Sumner and Simon Wotherspoon
参考文献----------References----------
<h3>See Also</h3>
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 2012-10-1 12:11:54
