ar.ols(stats)
ar.ols()所属R语言包：stats
Fit Autoregressive Models to Time Series by OLS
通过OLS适合自回归模型，时间序列
译者：生物统计家园网 机器人LoveR
描述----------Description----------
Fit an autoregressive time series model to the data by ordinary least squares, by default selecting the complexity by AIC.
适合普通最小二乘的数据序列模型的自回归时间，默认选择由AIC的复杂性。
用法----------Usage----------
ar.ols(x, aic = TRUE, order.max = NULL, na.action = na.fail,
demean = TRUE, intercept = demean, series, ...)
参数----------Arguments----------
参数：x
A univariate or multivariate time series.
一元或多元时间序列。
参数：aic
Logical flag. If TRUE then the Akaike Information Criterion is used to choose the order of the autoregressive model. If FALSE, the model of order order.max is fitted.
逻辑标志。如果TRUE然后用于赤池信息准则选择自回归模型的顺序。如果FALSE，为了order.max模型安装。
参数：order.max
Maximum order (or order) of model to fit. Defaults to 10*log10(N) where N is the number of observations.
以适应模型的最大订单（或订单）。默认为10*log10(N)N的若干意见。“
参数：na.action
function to be called to handle missing values.
函数被调用来处理缺失值。
参数：demean
should the AR model be for x minus its mean?
AR模型应该是x减去其平均值？
参数：intercept
should a separate intercept term be fitted?
应安装一个单独的截距项？
参数：series
names for the series. Defaults to deparse(substitute(x)).
系列名称。 deparse(substitute(x))默认。
参数：...
further arguments to be passed to or from methods.
进一步的参数被传递到或从方法。
Details
详情----------Details----------
ar.ols fits the general AR model to a possibly non-stationary and/or multivariate system of series x. The resulting unconstrained least squares estimates are consistent, even if some of the series are non-stationary and/or co-integrated. For definiteness, note that the AR coefficients have the sign in
ar.ols适合一般的AR模型可能非固定和/或多元系统的系列x。所产生的约束最小二乘估计是一致的，即使一些非固定和/或合作综合系列。定性，请注意，AR系数标志
where a[0] is zero unless intercept is true, and m is the sample mean if demean is true, zero otherwise.
a[0]是零，除非intercept是真实的，m样本均值demean如果是真实的，否则为零。
Order selection is done by AIC if aic is true. This is problematic, as ar.ols does not perform true maximum likelihood estimation. The AIC is computed as if the variance estimate (computed from the variance matrix of the residuals) were the MLE, omitting the determinant term from the likelihood. Note that this is not the same as the Gaussian likelihood evaluated at the estimated parameter values.
为了选择是由AIC aic如果是真实的。这是有问题的，ar.ols不执行真正的最大似然估计。 AIC的计算方差估计（从残差方差矩阵计算），如果是的MLE，行列式长期忽略的可能性。请注意，这不是为高斯的可能性进行评估估计的参数值相同。
Some care is needed if intercept is true and demean is false. Only use this is the series are roughly centred on zero. Otherwise the computations may be inaccurate or fail entirely.
如果intercept是真实的，demean是假的，一些需要照顾。只使用，这是系列的大致集中于零。否则，计算可能不准确或完全失败。
值----------Value----------
A list of class "ar" with the following elements:
一类"ar"以下内容的列表：
参数：order
The order of the fitted model. This is chosen by minimizing the AIC if aic=TRUE, otherwise it is order.max.
为了拟合模型。这是选择通过最大限度地减少了AIC如果aic=TRUE，否则它是order.max。
参数：ar
Estimated autoregression coefficients for the fitted model.
拟合模型估计的自回归系数。
参数：var.pred
The prediction variance: an estimate of the portion of the variance of the time series that is not explained by the autoregressive model.
预测方差：估计的时间序列，自回归模型的解释方差的部分。
参数：x.mean
The estimated mean (or zero if demean is false) of the series used in fitting and for use in prediction.
系列（或零demean如果是假的），估计平均在拟合和预测。
参数：x.intercept
The intercept in the model for x - x.mean, or zero if intercept is false.
如果的在x - x.mean模型的截距或零intercept是假的。
参数：aic
The differences in AIC between each model and the best-fitting model. Note that the latter can have an AIC of -Inf.
AIC中的每个模型和最佳拟合模型之间的差异。请注意，后者可以有一个-InfAIC的。
参数：n.used
The number of observations in the time series.
在时间序列观测。
参数：order.max
The value of the order.max argument.
order.max参数值。
参数：partialacf
NULL. For compatibility with ar.
NULL。对于与ar兼容性。
参数：resid
residuals from the fitted model, conditioning on the first order observations. The first order residuals are set to NA. If x is a time series, so is resid.
从拟合模型，空调第一order观测残差。第一order残差设置NA的。 x如果是一个时间系列，所以是resid。
参数：method
The character string "Unconstrained LS".
字符串"Unconstrained LS"。
参数：series
The name(s) of the time series.
时间序列的名称（S）。
参数：frequency
The frequency of the time series.
时间序列的频率。
参数：call
The matched call.
匹配的呼叫。
参数：asy.se.coef
The asymptotic-theory standard errors of the coefficient estimates.
系数估计的渐近理论的标准误差。
作者（S）----------Author(s)----------
Adrian Trapletti, Brian Ripley.
参考文献----------References----------
Analysis. Springer Verlag, NY, pp. 368–370.
参见----------See Also----------
ar
ar
举例----------Examples----------
ar(lh, method="burg")
ar.ols(lh)
ar.ols(lh, FALSE, 4) # fit ar(4)[适合AR（4）]
ar.ols(ts.union(BJsales, BJsales.lead))
x <- diff(log(EuStockMarkets))
ar.ols(x, order.max=6, demean=FALSE, intercept=TRUE)
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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发表于 2012-2-16 20:05:15
