Ajdf(Sim.DiffProc)
Ajdf()所属R语言包：Sim.DiffProc
Adjustment By F Distribution
F分布的调整，
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Adjusted your sample by the F law, estimated these parameters using the method of maximum likelihood, and calculating the Akaike information criterion for one or several fitted model objects for which a log-likelihood value can be obtained, according to the formula -2*log-likelihood + k*npar, where npar represents the number of parameters in the fitted model, and k = 2 for the usual AIC, and computes confidence intervals for one or more parameters in a fitted model (Law).
调整您的样品由F法，估计这些参数，使用最大似然法，和计算的Akaike信息准则的一个或几个可以以下方式获得的对数似然值的拟合模型对象，根据式-2 *log似然+的k * NPAR，其中NPAR表示拟合模型中的参数的数目，且k = 2为通常的AIC，并计算在拟合模型（法）为一个或多个参数的置信区间。
用法----------Usage----------
Ajdf(X, starts = list(df1 = 1, df2 = 1), leve = 0.95)
参数----------Arguments----------
参数：X
a numeric vector of the observed values.
所观察到的值的一个数值向量。
参数：starts
named list. Initial values for optimizer.
命名列表。优化的初始值。
参数：leve
the confidence level required.
所需的置信水平。
Details
详细信息----------Details----------
The optim optimizer is used to find the minimum of the negative log-likelihood. An approximate covariance matrix for the parameters is obtained by inverting the Hessian matrix at the optimum.
optim优化用于找到最小的负对数似然。反相在最佳的Hessian矩阵的近似协方差矩阵的参数通过以下方式获得。
For more detail consulted mle,confint,AIC.
更详细的咨询mle，confint，AIC。
R has the [dqpr]f functions to evaluate the density, the quantiles, and the cumulative distribution or generate pseudo random numbers from the F distribution.
R具有[dqpr]f评估的密度，位数，和累积分布函数，或产生从F分布的伪随机数。
值----------Value----------
参数：coef
Coefficients extracted from the model.
系数从模型中提取。
参数：AIC
A numeric value with the corresponding AIC.
与相应的AIC的数值。
参数：vcov
A matrix of the estimated covariances between the parameter estimates in the linear or non-linear predictor of the model.
甲之间的参数估计的协方差矩阵的估计中的线性或非线性预测模型。
参数：confint
A matrix (or vector) with columns giving lower and upper confidence limits for each parameter. These will be labelled as (1-level)/2 and 1 - (1-level)/2.
给每个参数的置信区间上限和下限的列的矩阵（或向量）。这些将被标记为（1级）/ 2和1 - （1级）/ 2。
（作者）----------Author(s)----------
Boukhetala Kamal, Guidoum Arsalane.
参见----------See Also----------
Ajdchisq Adjustment By Chi-Squared Distribution,Ajdexp Adjustment By Exponential Distribution, Ajdgamma Adjustment By Gamma Distribution,Ajdlognorm Adjustment By Log Normal Distribution, Ajdnorm Adjustment By Normal Distribution,Ajdt Adjustment By Student t Distribution, Ajdweibull Adjustment By Weibull Distribution,Ajdbeta Adjustment By Beta Distribution.
Ajdchisq卡方分布的调整，Ajdexp调整的指数分布，Ajdgamma的调整Gamma分布的，Ajdlognorm调整的数正态分布，Ajdnorm调整到正态分布，Ajdt由学生t分布的调整，Ajdweibull调整的Weibull分布，Ajdbeta调整的Beta分布。
实例----------Examples----------
X <- rf(100,df1=5,df2=5)
Ajdf(X, starts = list(df1 = 1, df2 = 1), leve = 0.95)
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 2012-9-30 02:16:18
