R语言 soil.spec包 ken.sto()函数中文帮助文档(中英文对照)

loveR

ken.sto(soil.spec)
ken.sto()所属R语言包：soil.spec

                                        Sample selection based on the Kennard-Stone algorithm
                                         根据的肯纳德石算法的样本选择

                                         译者：生物统计家园网 机器人LoveR

描述----------Description----------

The function chooses based on Euclidean distance measure most representative samples. One can (i) select a number or a percentage of a sample set or (ii) divide a sample set into calibration and representative validation set.
功能选择基于欧氏距离的措施，最有代表性的样品。一个可（i）选择一个数字或百分比的样本集，或（ii）进入校准和有代表性的验证集样本集划分。


用法----------Usage----------


ken.sto(inp, per = "TRUE", per.n = 0.3, num, va = "FALSE", sav = "TRUE", save.path = "NULL", output.name = "Sample selection")

## S3 method for class 'ken.sto':
plot(x,...)



参数----------Arguments----------

参数：inp
a numerical matrix or data.frame containing the input spectra
含有的输入光谱的数值矩阵或数据框


参数：per
a logical value indicating whether the selected samples should be a percentage (given in per.n) or a set number (given in num) of inp. The default "TRUE" takes a percentage.
一个逻辑值，该值指示是否选定的样品应该是一个百分比（per.n）或一组号码（在num）inp。默认"TRUE"的百分比。


参数：per.n
a numerical value between 0 and 1.
介于0和1之间的一个数值。


参数：num
a numerical value between 1 and the sample number minus 1.
1，样本数减1之间的一个数值。


参数：va
a logical value indicating whether to select samples out of inp or to divide them into a calibration and validation set.    <tr valign="top"><td>sav</td>
一个逻辑值，该值指示是否选择样本的inp或者把它们分为校准和验证集。 <tr valign="top"> <TD> sav</ TD>

a logical value indicating whether the function output shall be saved.
一个逻辑值，该值指示是否应保存功能输出。


参数：save.path
a character giving the path name where the function output shall be saved.
字符功能的输出应予以保存的路径名。


参数：output.name
a character giving the function output name, in case sav is "TRUE".
功能输出名称的字符的情况下，sav是"TRUE"。


参数：x
an object of class "ken.sto".
对象类"ken.sto"。


参数：...
additional arguments.
其他参数。


Details

详细信息----------Details----------

Sample selection is done following and adapted procedure from Kennard &amp; Stone (1969). It is a stepwise procedure by maximizing the Euclidean distance based on the important number of principal components to the objects already chosen. The number of important principal components is selected so that the increase in cumulative explained variance within the next three components is lower than 4 percent. The starting samples are the two extreme samples (most negative and positive ones) of the important principal components.
肯纳德和石（1969），样本选择以下和适应的过程。它是一个逐步的过程，根据已经选择的对象的主要组件上的重要的数字最大的欧几里得距离。重要的主成分的数量进行选择，使得在接下来的三个组成部分增加累积解释方差是低于4％。的起始的样品的两个极端重要的主成分的样本（最阴性和阳性的）。

per.n having a value of 0.4 while va equal to "FALSE" chooses 40 percent of the sample set. When va is equal to "TRUE" the validation set comprises 40 percent of the sample set.
per.n具有0.4的值，而va等于"FALSE"选择40％的样本集。当va等于"TRUE"验证设置，包括40％的样本集。

A graph is given back showing the selected samples in the principal component space (only the important PC's). This is the same graphic generated by plot.ken.sto.
一个图形的显示出所选择的样本空间（仅重要的PC）的主要组成部分。这是相同的图形，所产生的plot.ken.sto。


值----------Value----------

ken.sto returns a list with class "ken.sto" containing the following components:  <table summary="R valueblock"> <tr valign="top"><td>Calibration and validation set</td> <td> the logical object va.</td></tr> <tr valign="top"><td>Number important PC</td> <td> integer giving the number of chosen important components - important for choosing the starting samples.</td></tr> <tr valign="top"><td>PC space important PC</td> <td> score value matrix of important principal components.</td></tr> <tr valign="top"><td>Chosen samples names</td> <td> chosen sample names when va equal to "FALSE".</td></tr> <tr valign="top"><td>Chosen row number</td> <td> chosen row numbers when va equal to "FALSE".</td></tr> <tr valign="top"><td>Chosen calibration sample names</td> <td> chosen calibration sample names when va equal to "TRUE".</td></tr> <tr valign="top"><td>Chosen calibration row number</td> <td> chosen calibration row numbers when va equal to "TRUE".</td></tr> <tr valign="top"><td>Chosen validation sample names</td> <td> chosen validation sample names when va equal to "TRUE".</td></tr> <tr valign="top"><td>Chosen validation  row number</td> <td> chosen validation row numbers when va equal to "TRUE".</td></tr></table>
ken.sto返回一个列表类"ken.sto"包含以下组件：<table summary="R valueblock"> <tr valign="top"> <TD> Calibration and validation set</ TD> < TD>的逻辑对象va。</ TD> </ TR> <tr valign="top"> <TD>Number important PC </ TD> <TD>整数，给出了选择的重要组成部分 - 重要的是选择样品。</ TD> </ TR> <tr valign="top"> <TD> PC space important PC </ TD> <TD>得分值矩阵的重要主要组成部分。</ TD > </ TR> <tr valign="top"> <TD>Chosen samples names </ TD> <TD>选择样品名称va等于"FALSE"。</ TD> < / TR> <tr valign="top"> <TD> Chosen row number </ TD> <TD>选择的行数时va等于"FALSE"。</ TD> </ TR > <tr valign="top"> <TD> Chosen calibration sample names </ TD> <TD>选择校准样品名称，当va等于"TRUE"。</ TD> </ TR> <tr valign="top"> <TD> Chosen calibration row number </ TD> <TD>选择校准行号时va等于"TRUE"。</ TD> </ TR> < TR VALIGN =“顶”> <TD> Chosen validation sample names </ TD> <TD>选择验证样品名称，当va等于"TRUE"。</ TD> </ TR> <TR VALIGN =“”> <TD> Chosen validation  row number </ TD> <TD>选择验证的行数，当va等于"TRUE"。</ TD> </ TR> </表>


（作者）----------Author(s)----------


Thomas Terhoeven-Urselmans



参考文献----------References----------

Kennard, R. W. and Stone, L. A. (1969) Computer aided design of experiments. Technometrics 11(1), 137-148.
转载请注明:出自 生物统计家园网(http://www.biostatistic.net)。


注：
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