英文字典中文字典


英文字典中文字典51ZiDian.com



中文字典辞典   英文字典 a   b   c   d   e   f   g   h   i   j   k   l   m   n   o   p   q   r   s   t   u   v   w   x   y   z       







请输入英文单字，中文词皆可：

estimator    音标拼音: [ɛst'ɪmətɚ] ['ɛstɪm,etɚ]
n. 估计者

安装中文字典英文字典查询工具!


中文字典英文字典工具:
选择颜色:
输入中英文单字

































































英文字典中文字典相关资料:


  • What is the relation between estimator and estimate?
    In Lehmann's formulation, almost any formula can be an estimator of almost any property There is no inherent mathematical link between an estimator and an estimand However, we can assess--in advance--the chance that an estimator will be reasonably close to the quantity it is intended to estimate
  • Variance of sample median - Cross Validated
    The HL median estimate is especially simple for small samples of size n, just compute all possible two point (including repeats) averages From these n(n+1) 2 new constructs, compute the HL Median Estimator as the usual sample median Now, per the same Wikipedia article on the median, the cited variance of the median 1 (4*n*f(median)*f(median))
  • Notation in statistics (parameter estimator estimate)
    We use an estimator which books usually denote by $\widehat{\theta}$ The estimator is a random variable
  • What is the difference between estimation and prediction?
    purpose: an estimator seeks to know a property of the true state of nature, while a prediction seeks to guess the outcome of a random variable; and uncertainty: a predictor usually has larger uncertainty than a related estimator, due to the added uncertainty in the outcome of that random variable Well-documented and -described predictors
  • What is the difference between a consistent estimator and an unbiased . . .
    An estimator is unbiased if, on average, it hits the true parameter value That is, the mean of the sampling distribution of the estimator is equal to the true parameter value The two are not equivalent: Unbiasedness is a statement about the expected value of the sampling distribution of the estimator
  • ML vs WLSMV: which is better for categorical data and why?
    The most common estimator used for this approach is some form of diagonally weighted least squares (DWLS) WLSMV falls under the DWLS umbrella, though it is not technically an estimator DWLS is the estimator, and calling WLSMV in a software package (e g , lavaan or Mplus ) tells the program to report robust standard errors and to use a
  • estimation - The distribution of an estimator - Cross Validated
    The bootstrap often works well in small samples The reason small samples are mentioned is because you can't rely on the asymptotic normality when the sample size is small The bootstrap will approximate the sampling distribution for the m-estimator at the given fixed sample size





中文字典-英文字典  2005-2009