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R语言 VGAM包 uqo.control()函数中文帮助文档(中英文对照)

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发表于 2012-10-1 15:56:02 | 显示全部楼层 |阅读模式
uqo.control(VGAM)
uqo.control()所属R语言包:VGAM

                                         Control Function for UQO models
                                         控制功能UQO模型

                                         译者:生物统计家园网 机器人LoveR

描述----------Description----------

Algorithmic constants and parameters for an unconstrained quadratic ordination (UQO) model, by fitting a quadratic unconstrained vector generalized additive model (QU-VGLM), are set using this function. It is the control function of uqo.
算法的常数和参数为一个无约束的二次协调(UQO)模型,通过拟合的二次无约束向量广义加性模型(QU-VGLM),使用此功能。控制功能uqo。


用法----------Usage----------


uqo.control(Rank=1, Bestof = if (length(lvstart) &&
            !jitter.sitescores) 1 else 10, CA1 = FALSE, Crow1positive
            = TRUE, epsilon = 1.0e-07, EqualTolerances = ITolerances,
            Etamat.colmax = 10, GradientFunction=TRUE, Hstep = 0.001,
            isdlv = rep(c(2, 1, rep(0.5, len=Rank)), len=Rank),
            ITolerances = FALSE, lvstart = NULL, jitter.sitescores
            = FALSE, maxitl = 40, Maxit.optim = 250, MUXfactor =
            rep(3, length=Rank), optim.maxit = 20, nRmax = 250,
            SD.sitescores = 1.0, SmallNo = 5.0e-13, trace = TRUE,
            Use.Init.Poisson.QO=TRUE, ...)



参数----------Arguments----------

参数:Rank
The numerical rank R of the model, i.e., the number of latent variables or ordination axes. Currently only R=1 is recommended.  
数值秩R的模式,即,的潜变量或协调轴的数量。目前只有R=1建议。


参数:Bestof
Integer. The best of Bestof models fitted is returned. This argument helps guard against local solutions by (hopefully) finding the global solution from many fits. The argument has value 1 if an initial value for the site scores is inputted using lvstart.  
整数。 Bestof车型配备最好的返回。此参数有助于防止对本地解决方案(希望)发现许多适合全球性的解决方案。参数值为1的初始值#输入lvstart的。


参数:CA1
Logical. If TRUE the site scores from a correspondence analysis (CA) are computed and used on the first axis as initial values. Both CA1 and Use.Init.Poisson.QO cannot both be TRUE.  
逻辑。如果TRUE网站分数从对应分析(CA)的计算和用作为初始值的第一轴线上。这两个CA1和Use.Init.Poisson.QO不能同时是TRUE的。


参数:Crow1positive
Logical vector of length Rank (recycled if necessary): are the elements of the first row of the latent variable matrix nu positive? For example, if Rank is 2, then specifying Crow1positive=c(FALSE, TRUE) will force the first site score's first element to be negative, and the first site score's second element to be positive.  Note that there is no C matrix with UQO, but the argument's name comes from qrrvglm.control and is left unchanged for convenience.  
逻辑的矢量的长度Rank(再循环如果必要的话):是的第一行中的元素的潜变量矩阵nu阳性?例如,如果Rank是2,然后指定Crow1positive=c(FALSE, TRUE)将迫使第一现场评分的第一个元素是消极的,第一个站点得分的第二个元素是积极的。请注意有没有C矩阵UQO的,但参数的名称来自qrrvglm.control和为方便起见,将保持不变。


参数:epsilon
Positive numeric. Used to test for convergence for GLMs fitted in FORTRAN.  Larger values mean a loosening of the convergence criterion.  
正数值。用于收敛GLMS安装在FORTRAN测试。值越大,意味着松动的收敛准则。


参数:EqualTolerances
Logical indicating whether each (quadratic) predictor will have equal tolerances. Setting EqualTolerances=TRUE can help avoid numerical problems, especially with binary data. Note that the estimated (common) tolerance matrix may or may not be positive-definite. If it is, then it can be scaled to the R x R identity matrix.  Setting ITolerances=TRUE will fit a common R x R identity matrix as the tolerance matrix to the data, but this is model-driven rather than being data-driven because it forces bell-shaped curves/surfaces onto the data.  If the estimated (common) tolerance matrix happens to be positive-definite, then this model is essentially equivalent to the model with ITolerances=TRUE. See Details in cqo and qrrvglm.control for more details.  
逻辑表明,是否每个(二次)的预测都享有平等的公差。设置EqualTolerances=TRUE可以帮助避免数值的问题,尤其是二进制数据。请注意,估计的(共同)容许矩阵可能是或可能不是正定的。如果是的话,那么它可以扩展到RXR单位矩阵。设定ITolerances=TRUE适合一个共同的RXR身份的耐受性矩阵,矩阵的数据,但是这是模型驱动的,而不是数据驱动的,因为它迫使钟形曲线/表面上的数据。如果估计的(普通)的耐受性矩阵恰好是正定的,那么这个模型本质上是相同的模型ITolerances=TRUE。有关详细信息,请参阅详细的cqo和qrrvglm.control。


参数:Etamat.colmax
Positive integer, no smaller than Rank.  Controls the amount of memory used by .Init.Poisson.QO().  It is the maximum number of columns allowed for the pseudo-response and its weights. In general, the larger the value, the better the initial value. Used only if Use.Init.Poisson.QO=TRUE.  
正整数,不小于Rank。控制使用的内存量的.Init.Poisson.QO()。是允许为伪响应及其权重的列的最大数目。在一般情况下,该值越大,更好的初始值。用只有Use.Init.Poisson.QO=TRUE。


参数:GradientFunction
Logical. Whether optim's argument gr is used or not, i.e., to compute gradient values.  The default value is usually faster on most problems.  
逻辑。无论optim的说法gr使用与否,即,计算梯度值。默认值通常是更快的大多数问题。


参数:Hstep
Positive value. Used as the step size in the finite difference approximation to the derivatives by optim.  
正值。作为步长的有限差分近似的衍生工具optim。


参数:isdlv
Initial standard deviations for the latent variables (site scores). Numeric, positive and of length R (recycled if necessary). This argument is used only if ITolerances=TRUE.  Used by .Init.Poisson.QO() to obtain initial values for the constrained coefficients C adjusted to a reasonable value. It adjusts the spread of the site scores relative to a common species tolerance of 1 for each ordination axis.  A value between 0.5 and 10 is recommended; a value such as 10 means that the range of the environmental space is very large relative to the niche width of the species.  The successive values should decrease because the first ordination axis should have the most spread of site scores, followed by the second ordination axis, etc.  
最初的标准偏差的潜在变量(网站评分)。数字,积极长度R(回收如果必要的话)。这种说法是只有ITolerances=TRUE。使用的.Init.Poisson.QO()获得的初始值约束系数C调整到一个合理的值。它调整的部位相对于一个共同的种为每个协调轴公差为1的分数的蔓延。 0.5和10之间的一个值建议值,如10,表示相对于该物种的生态位宽度范围内的环境空间是非常大的。的连续值应该减少,因为第一排序轴应具有最蔓延站点分数,然后由所述第二排序轴等


参数:ITolerances
Logical. If TRUE then the (common) tolerance matrix is the R x R identity matrix by definition.  Note that ITolerances=TRUE implies EqualTolerances=TRUE, but not vice versa.  Internally, the quadratic terms will be treated as offsets (in GLM jargon) and so the models can potentially be fitted very efficiently.  See Details in cqo and qrrvglm.control for more details. more details.  The success of ITolerances=TRUE often depends on suitable values for isdlv and/or MUXfactor.  
逻辑。如果TRUE(普通)的耐受性矩阵是RXR的身份矩阵的定义。需要注意的是ITolerances=TRUE意味着EqualTolerances=TRUE,但反之则不然。在内部,二次项将被视为偏移(GLM术语),这样的模式可能会被安装非常有效的。有关详细信息,请参阅详细的cqo和qrrvglm.control。更多的细节。 ITolerances=TRUE的成功往往取决于isdlv和/或MUXfactor合适的值。


参数:lvstart
Optional matrix of initial values of the site scores. If given, the matrix must be n by R, where n is the number of sites and R is the rank.  This argument overrides the arguments Use.Init.Poisson.QO and CA1. Good possibilities for lvstart are the site scores from a constrained ordination, e.g., from cqo.  
可选的站点得分矩阵的初始值。如果给定矩阵必须是nR,其中n的网站数量和R是排名。该参数将取代的参数Use.Init.Poisson.QO和CA1。很好的机会为lvstart是从约束的协调,例如,从cqo#。


参数:jitter.sitescores
Logical. If TRUE the initial values for the site scores are jittered to add a random element to the starting values.  
逻辑。如果TRUE的站点得分的初始值,抖动添加一个随机元素的开始值。


参数:maxitl
Positive integer.  Number of iterations allowed for the IRLS algorithm implemented in the compiled code.  
正整数。允许IRLS编译后的代码中实现的算法的迭代数目。


参数:Maxit.optim
Positive integer.  Number of iterations given to the function optim at each of the optim.maxit iterations.  
正整数。给函数的迭代数目optim在每个optim.maxit迭代。


参数:MUXfactor
Multiplication factor for detecting large offset values.  Numeric, positive and of length R (recycled if necessary).  This argument is used only if ITolerances=TRUE. Offsets are -0.5 multiplied by the sum of the squares of all R latent variable values. If the latent variable values are too large then this will result in numerical problems. By too large, it is meant that the standard deviation of the latent variable values are greater than MUXfactor[r] * isdlv[r] for r=1:Rank (this is why centering and scaling all the numerical predictor variables in x_2 is recommended).  A value about 3 or 4 is recommended. If failure to converge occurs, try a slightly lower value.  
用于检测的大的偏移值的倍增因子。数字,积极长度R(回收如果必要的话)。这种说法是只有ITolerances=TRUE。偏移量是-0.5乘以所有R潜变量值的平方的总和。如果潜变量值过大,那么这将导致在数值的问题。过大,它的意思是潜变量的值的标准偏差大于MUXfactor[r] * isdlv[r]的r=1:Rank(这就是为什么所有的数值预测变量的中心和缩放x_2建议)。推荐值约3或4。如果出现收敛失败,请尝试使用较低的值。


参数:optim.maxit
Positive integer.  Number of times optim is invoked.   
正整数。次optim数被调用。


参数:nRmax
Positive integer.  If the number of parameters making up the latent variable values (n multiplied by R) is greater than this argument then a conjugate-gradients algorithm is used, otherwise a quasi-Newton algorithm is used by optim. The conjugate-gradients method is more suitable when the number of parameters is large because it requires less memory.  
正整数。如果潜变量的值(n乘以R)的参数的数量是大于这个参数的共轭梯度算法,否则拟牛顿算法所使用的optim。共轭梯度法更适合当参数的数目大,因为它需要较少的内存。


参数:SD.sitescores
Numeric. Standard deviation of the initial values of the site scores, which are generated from a normal distribution.  
数字。的站点的分数,所产生的正常分布的初始值的标准偏差。


参数:SmallNo
Positive numeric between .Machine$double.eps and 0.0001. Used to avoid under- or over-flow in the IRLS algorithm.  
正数之间.Machine$double.eps和0.0001。用于避免在IRLS算法不足或过度流动。


参数:trace
Logical indicating if output should be produced for each iteration.  
逻辑表明,如果输出应为每个迭代。


参数:Use.Init.Poisson.QO
Logical. If TRUE then the function .Init.Poisson.QO() is used to obtain initial values for the site scores.  If FALSE then random numbers are used instead.  Both CA1 and Use.Init.Poisson.QO cannot both be TRUE.  
逻辑。如果TRUE然后.Init.Poisson.QO()功能的使用为网站评分中获得的初始值。如果FALSE然后随机数来代替。这两个CA1和Use.Init.Poisson.QO不能同时是TRUE的。


参数:...
Ignored at present.  
目前被忽略。


Details

详细信息----------Details----------

The algorithm currently used by uqo is unsophisticated and fails often. Improvements will hopefully be made soon.
该算法目前使用uqo的是不成熟的,经常出现故障。将有望很快做出改进。

See cqo and qrrvglm.control for more details that are equally pertinent to UQO.
cqo和qrrvglm.control更多的细节,也同样相关的UQO。

To reduce the number of parameters being estimated, setting ITolerances = TRUE or EqualTolerances = TRUE is advised.
为了减少所估计的参数,设置ITolerances = TRUE或EqualTolerances = TRUE建议。


值----------Value----------

A list with the components corresponding to its arguments, after some basic error checking.
列表给它的参数相对应的部件后,一些基本的错误检查。


警告----------Warning ----------

This function is currently very sensitive to initial values. Setting Bestof some reasonably large integer is recommended.
此功能目前为初始值非常敏感。设置Bestof一些相当大的整数建议。


注意----------Note----------

This is a difficult optimization problem, and the current algorithm needs to be improved.
这是一个困难的最优化问题,目前的算法,需要加以改进。


(作者)----------Author(s)----------


T. W. Yee



参考文献----------References----------

Constrained additive ordination. Ecology, 87, 203–213.

参见----------See Also----------

uqo.
uqo。


实例----------Examples----------


uqo.control()

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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