nlm(stats)
nlm()所属R语言包：stats
Non-Linear Minimization
非线性最小化
译者：生物统计家园网 机器人LoveR
描述----------Description----------
This function carries out a minimization of the function f using a Newton-type algorithm. See the references for details.
此功能进行功能f使用牛顿型算法的最小化。有关详细信息，请参阅参考。
用法----------Usage----------
nlm(f, p, ..., hessian = FALSE, typsize = rep(1, length(p)),
fscale = 1, print.level = 0, ndigit = 12, gradtol = 1e-6,
stepmax = max(1000 * sqrt(sum((p/typsize)^2)), 1000),
steptol = 1e-6, iterlim = 100, check.analyticals = TRUE)
参数----------Arguments----------
参数：f
the function to be minimized. If the function value has an attribute called gradient or both gradient and hessian attributes, these will be used in the calculation of updated parameter values. Otherwise, numerical derivatives are used. deriv returns a function with suitable gradient attribute. This should be a function of a vector of the length of p followed by any other arguments specified by the ... argument.
最小化的功能。如果函数值的属性，称为gradient都gradient和hessian属性，这些将用于更新的参数值计算。否则，数值衍生工具的使用。 deriv返回一个合适的gradient属性的功能。这应该是一个向量一个p...参数指定任何其他参数跟着的长度的功能。
参数：p
starting parameter values for the minimization.
最小的参数值。
参数：...
additional arguments to f.
f额外的参数。
参数：hessian
if TRUE, the hessian of f at the minimum is returned.
如果TRUE，f最低返回麻袋。
参数：typsize
an estimate of the size of each parameter at the minimum.
在最低估计每个参数的大小。
参数：fscale
an estimate of the size of f at the minimum.
的最低f的大小估计。
参数：print.level
this argument determines the level of printing which is done during the minimization process. The default value of 0 means that no printing occurs, a value of 1 means that initial and final details are printed and a value of 2 means that full tracing information is printed.
这个参数决定了印刷的水平，这是最小化过程中完成。默认值0意味着没有出现印刷，“1是指，最初和最后的细节印和价值2手段，全面跟踪信息打印值。
参数：ndigit
the number of significant digits in the function f.
在功能f有效位数的号码。
参数：gradtol
a positive scalar giving the tolerance at which the scaled gradient is considered close enough to zero to terminate the algorithm. The scaled gradient is a measure of the relative change in f in each direction p[i] divided by the relative change in p[i].
给予宽容规模梯度被认为是足够接近零，以终止该算法的一个正标量。规模的梯度是一个相对变化的措施f在每个方向p[i]由p[i]的相对变化分歧。
参数：stepmax
a positive scalar which gives the maximum allowable scaled step length. stepmax is used to prevent steps which would cause the optimization function to overflow, to prevent the algorithm from leaving the area of interest in parameter space, or to detect divergence in the algorithm. stepmax would be chosen small enough to prevent the first two of these occurrences, but should be larger than any anticipated reasonable step.
积极标了允许的最大规模的步长。 stepmax是用来防止措施，这将导致溢出的优化功能，以防止离开感兴趣的领域，在参数空间的算法，或检测算法的分歧。 stepmax将选择足够小，以防止这些事件的前两个，但应该大于任何预期的合理步骤。
参数：steptol
A positive scalar providing the minimum allowable relative step length.
提供一个正标量允许的最小相对步长。
参数：iterlim
a positive integer specifying the maximum number of iterations to be performed before the program is terminated.
一个正整数，指定程序之前要进行迭代的最大数量将被终止。
参数：check.analyticals
a logical scalar specifying whether the analytic gradients and Hessians, if they are supplied, should be checked against numerical derivatives at the initial parameter values. This can help detect incorrectly formulated gradients or Hessians.
逻辑标量指定是否解析梯度和粗麻布，如果他们提供的，应当检查对数值衍生工具的初始参数值。这可以帮助检测错误制定的梯度或粗麻布。
Details
详情----------Details----------
Note that arguments after ... must be matched exactly.
请注意，后...参数必须完全匹配。
If a gradient or hessian is supplied but evaluates to the wrong mode or length, it will be ignored if check.analyticals = TRUE (the default) with a warning. The hessian is not even checked unless the gradient is present and passes the sanity checks.
如果渐变或麻袋提供，但计算错误的模式或长度，它会被忽略，如果check.analyticals = TRUE（默认）一个警告。的Hessian甚至不检查，除非梯度存在，并通过健康检查。
From the three methods available in the original source, we always use method “1” which is line search.
从三种方法可在原始的，我们总是使用方法“1”，这是网上搜索。
The functions supplied must always return finite (including not NA and not NaN) values.
提供的功能，必须始终有限（包括不NA而不是NaN）值返回。
值----------Value----------
A list containing the following components:
一个列表，包含以下组件：
参数：minimum
the value of the estimated minimum of f.
f估计最低值。
参数：estimate
the point at which the minimum value of f is obtained.
时获得的最低值f点。
参数：gradient
the gradient at the estimated minimum of f.
在f估计最低的梯度。
参数：hessian
the hessian at the estimated minimum of f (if requested).
麻袋f（如果要求）估计最低。
参数：code
an integer indicating why the optimization process terminated.
一个整数，指示的优化进程终止的原因。
1:relative gradient is close to zero, current iterate is probably solution.
1：相对梯度接近于零，当前迭代是可能的解决方案。
2:successive iterates within tolerance, current iterate is probably solution.
2：连续迭代公差范围内，当前迭代是可能的解决方案。
3:last global step failed to locate a point lower than estimate. Either estimate is an approximate local minimum of the function or steptol is too small.
3：全球最后一个步骤失败，找到一个点，比estimate较低。要么estimate是一个近似的功能或steptol太小当地最低。
4:iteration limit exceeded.
4迭代超限。
5:maximum step size stepmax exceeded five consecutive times. Either the function is unbounded below, becomes asymptotic to a finite value from above in some direction or stepmax is too small.
5：最大步长stepmax连续超过5倍。要么下面是无限的功能，成为渐近有限值从上述一些方向或stepmax太小。
参数：iterations
the number of iterations performed.
执行的迭代次数。
参考文献----------References----------
Unconstrained Optimization and Nonlinear Equations. Prentice-Hall, Englewood Cliffs, NJ.
system of algorithms for unconstrained minimization. ACM Trans. Math. Software, 11, 419–440.
参见----------See Also----------
optim and nlminb.
optim和nlminb。
constrOptim for constrained optimization, optimize for one-dimensional minimization and uniroot for root finding. deriv to calculate analytical derivatives.
constrOptim约束优化，optimize一维的最小化和uniroot寻根。 deriv计算分析衍生物。
For nonlinear regression, nls may be better.
非线性回归，nls可能是更好的。
举例----------Examples----------
f <- function(x) sum((x-1:length(x))^2)
nlm(f, c(10,10))
nlm(f, c(10,10), print.level = 2)
utils::str(nlm(f, c(5), hessian = TRUE))
f <- function(x, a) sum((x-a)^2)
nlm(f, c(10,10), a=c(3,5))
f <- function(x, a)
{
res <- sum((x-a)^2)
attr(res, "gradient") <- 2*(x-a)
res
}
nlm(f, c(10,10), a=c(3,5))
## more examples, including the use of derivatives.[＃更多的例子，包括衍生工具的使用。]
## Not run: demo(nlm)[＃无法运行演示（NLM）]
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 2012-2-17 09:57:03
