R语言 SpherWave包 swthresh()函数中文帮助文档(中英文对照)

loveR

swthresh(SpherWave)
swthresh()所属R语言包：SpherWave

                                        Thresholding of Spherical Wavelet Decomposition (‘swd’) Object
                                         阈值的的球面小波分解（社署）对象

                                         译者：生物统计家园网 机器人LoveR

描述----------Description----------

This function performs various ways to threshold a "swd" class object.
这个函数执行阈值“社署”类对象的各种方法。


用法----------Usage----------


swthresh(swd, policy, by.level, type, nthresh, value = 0.1,
Q = 0.05)



参数----------Arguments----------

参数：swd
an object of class "swd"
对象类“社署”


参数：policy
threshold technique. At present the possible policies are ""universal"", ""probability"", ""fdr"", ""Lorentz"" and ""sure"".
阈值技术。目前的政策是“通用”的“，”概率“，”FDR“，”洛伦兹“和”确定“。


参数：by.level
If FALSE, then perform a global threshold. If TRUE, a thresholding value is computed and applied separately to each resolution level.
如果为FALSE，则执行一个全球性的阈值。如果为true，阈值值计算，并分别应用到每个分辨率级别。


参数：type
the type of thresholding. This can be ""hard"", ""soft"" or ""Lorentz"".
的阈值的类型。这可以是“硬”“，”软“或”“洛伦兹”。


参数：nthresh
the number of resolution levels to be thresholded in the decomposition
要在分解阈值的数目的分辨率水平


参数：value
the user supplied threshold represented by quantile level for ""probability"" policy
用户提供的位数水平为代表的“概率阈值”政策


参数：Q
parameter for the false discovery rate of ""fdr"" policy
“FDR”政策的错误发现率的参数


Details

详细信息----------Details----------

This function thresholds or shrinks details stored in a "swd" object and returns the thresholded details in a modified "swd" object. For level-dependent thresholding, ""universal"", ""Lorentz"" and ""fdr"" are provided. Only hard type thresholding is proper for ""probability"" thresholding. Also note that only soft type thresholding is proper for ""sure"" thresholding.
此功能的阈值或缩小细节中“社署的对象，存储和返回阈值的详细信息在修改后的”社署“对象。水平依赖阈值，“通用”“，”“洛伦兹”和“FDR”“。只有硬型阈值是正确的“”概率“阈值”。另外请注意，只有软式“确保”阈值阈值是正确的。


值----------Value----------

An object of class "swd". This object is a list with the following components.  <table summary="R valueblock"> <tr valign="top"><td>obs</td> <td> observations</td></tr> <tr valign="top"><td>latlon</td> <td> grid points of observation sites in degree</td></tr> <tr valign="top"><td>netlab</td> <td> vector of labels representing sub-networks</td></tr>  <tr valign="top"><td>eta</td> <td> bandwidth parameters for Poisson kernel</td></tr>  <tr valign="top"><td>method</td> <td> extrapolation methods, ""ls"" or ""pls""</td></tr>  <tr valign="top"><td>approx</td> <td> if TRUE, approximation is used.</td></tr> <tr valign="top"><td>grid.size</td> <td> grid size (latitude, longitude) of extrapolation site</td></tr>  <tr valign="top"><td>lambda</td> <td> smoothing parameter for penalized least squares method</td></tr>  <tr valign="top"><td>p0</td> <td> starting level for extrapolation. Resolution levels p0+1, \ldots, L is used for extrapolation.</td></tr>  <tr valign="top"><td>gridlon</td> <td> longitudes of extrapolation sites in degree</td></tr> <tr valign="top"><td>gridlat</td> <td> latitudes of extrapolation sites in degree</td></tr> <tr valign="top"><td>nlevels</td> <td> the number of multi-resolution levels</td></tr>  <tr valign="top"><td>coeff</td> <td> interpolation coefficients</td></tr> <tr valign="top"><td>field</td> <td> extrapolation on grid.size</td></tr> <tr valign="top"><td>density1</td> <td> density of SBF</td></tr> <tr valign="top"><td>latlim</td> <td> range of latitudes in degree</td></tr> <tr valign="top"><td>lonlim</td> <td> range of longitudes in degree</td></tr> <tr valign="top"><td>global</td> <td> List of successively smoothed data</td></tr> <tr valign="top"><td>density</td> <td> density of SW coefficients</td></tr> <tr valign="top"><td>detail</td> <td> List of details at different resolution levels</td></tr> <tr valign="top"><td>swcoeff</td> <td> spherical wavelet coefficients</td></tr> <tr valign="top"><td>thresh.info</td> <td> thresholding information and ranges of local components before thresholding</td></tr> </table>
的对象类社署。此对象是一个具有下列组件列表。 <table summary="R valueblock"> <tr valign="top"> <TD> obs</ TD> <TD>的意见</ TD> </ TR> <tr valign="top"> < latlon TD> </ TD> <TD>网格点的观测点度</ TD> </ TR> <tr valign="top"> <TD> netlab</ TD> < TD>矢量表示子网络的标签</ TD> </ TR> <tr valign="top"> <TD>eta </ TD> <TD>带宽参数Poisson核</ TD> < / TR> <tr valign="top"> <TD> method</ TD> <TD>外推法“，”LS“或”PLS“</ TD> </ TR> <tr valign="top"> <TD> approx </ TD> <TD>如果为TRUE，使用近似。</ TD> </ TR> <tr valign="top"> <TD >grid.size</ TD> <TD>网格尺寸（纬度，经度）外推网站</ TD> </ TR> <tr valign="top"> <TD>lambda</ TD > <TD>平滑参数补偿最小二乘法</ TD> </ TR> <tr valign="top"> <TD> p0 </ TD> <TD>开始外推。分辨率级别p0+1, \ldots, L使用外推。</ TD> </ TR> <tr valign="top"> <TD>gridlon </ TD> <TD>东经度的外推网站< / TD> </ TR> <tr valign="top"> <TD> gridlat </ TD> <TD>纬度程度的外推网站</ TD> </ TR> <TR VALIGN =“顶部“> <TD> nlevels </ TD> <TD>数多分辨率水平</ TD> </ TR> <tr valign="top"> <TD>coeff</ TD> <TD>插值系数</ TD> </ TR> <tr valign="top"> <TD> field </ TD> <TD>外推法grid.size </ TD> </ TR > <tr valign="top"> <TD> density1 </ TD> <TD>密度SBF </ TD> </ TR> <tr valign="top"> <TD>latlim </ TD> <TD>范围的纬度度</ TD> </ TR> <tr valign="top"> <TD>lonlim </ TD> <TD>范围内的经度度< / TD> </ TR> <tr valign="top"> <TD> global </ TD> <TD>连续平滑的数据列表</ TD> </ TR> <TR VALIGN =“顶” > <TD> density </ TD> <TD>密度的SW系数</ TD> </ TR> <tr valign="top"> <TD> detail</ TD> <TD >列表的细节在不同的分辨率级别</ TD> </ TR> <tr valign="top"> <TD> swcoeff </ TD> <TD>球面小波系数</ TD> </ TR> <tr valign="top"> <TD> thresh.info </ TD> <TD>阈值信息和本地组件之前阈值范围</ TD> </ TR> </ TABLE>


参考文献----------References----------

Oh, H-S. and Li, T-H. (2004) Estimation of global temperature fields from scattered observations by  a spherical-wavelet-based spatially adaptive method. Journal of the Royal Statistical Society Ser. B, 66, 221&ndash;238.

参见----------See Also----------

sbf, swd, swr.
sbf，swd，swr。


实例----------Examples----------


### Observations of year 1967[＃＃1967年的观察]
#data(temperature)[数据（温度）]
#names(temperature)[名称（温度）]

# Temperatures on 939 weather stations of year 1967    [1967年的939个气象站的温度]
#temp67 &lt;- temperature$obs[temperature$year == 1967] [temp67 < - 温度美元OBS [温度年== 1967]]
# Locations of 939 weather stations    [939个气象站的位置]
#latlon &lt;- temperature$latlon[temperature$year == 1967, ][latlon < - 的温度美元latlon [温度年== 1967年]]

### Network design by BUD[＃＃网络设计BUD]
#data(netlab)[数据（NETLAB）]

### Bandwidth for Poisson kernel[＃＃泊松核的带宽]
#eta &lt;- c(0.961, 0.923, 0.852, 0.723, 0.506)[ETA  -  C（0.961，0.923，0.852，0.723，0.506）]

### SBF representation of the observations by pls[＃＃的SBF表示，观察PLS]
#out.pls &lt;- sbf(obs=temp67, latlon=latlon, netlab=netlab, eta=eta, [SBF（OBS = temp67，latlon latlon，NETLAB = NETLAB，η= ETA，out.pls < - ]
#    method="pls", grid.size=c(50, 100), lambda=0.89)[方法=“PLS”，grid.size = C（50，100），λ= 0.89）]

### Decomposition[＃＃分解]
#out.dpls &lt;- swd(out.pls)[out.dpls < - 社署（out.pls）]

### Thresholding[＃＃阈值]
#out.univ &lt;- swthresh(out.dpls, policy="universal", by.level=TRUE, [out.univ < -  swthresh（out.dpls，政策=“通用”，by.level = TRUE，]
#    type="hard", nthresh=4) [=“硬”，nthresh = 4）]

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。