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fiducial    
a. 基准的,根据信仰的,信托的

基准的,根据信仰的,信托的

fiducial
adj 1: relating to or of the nature of a legal trust (i.e. the
holding of something in trust for another); "a fiduciary
contract"; "in a fiduciary capacity"; "fiducial power"
[synonym: {fiduciary}, {fiducial}]
2: used as a fixed standard of reference for comparison or
measurement; "a fiducial point"
3: based on trust

Fiducial \Fi*du"cial\, a. [L. fiducia trust, confidence; akin to
fides faith. See {Faith}.]
1. Having faith or trust; confident; undoubting; firm.
"Fiducial reliance on the promises of God." --Hammond.
[1913 Webster]

2. Having the nature of a trust; fiduciary; as, fiducial
power. --Spelman.
[1913 Webster]

{Fiducial edge} (Astron. & Surv.), the straight edge of the
alidade or ruler along which a straight line is to be
drawn.

{Fiducial line} or {Fiducial point} (Math. & Physics.), a
line or point of reference, as for setting a graduated
circle or scale used for measurements.
[1913 Webster]


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  • What does fiducial mean (in the context of statistics)?
    In the view of fiducial inference, $\lambda$ is also a random variable but it does not have a prior distribution, just a fiducial distribution that depends only on $(x_1, \ldots, x_n)$ To follow up on the example above, the fiducial distribution is $\lambda^n e^{-\lambda(x_1+\ldots+x_n)}$ This is the same as the likelihood, except that it is
  • Understanding the Behrens–Fisher problem - Cross Validated
    Although the fiducial argument is generally considered to be Fisher's only big flaw and has been discredited, the approach is not totally dead and there has been new research in it in recent years I think that fiducial inference was Fisher's way to try to be an "objective Bayesian"
  • Multiple comparisons with p-value corrections of fiducial limits?
    LD50 values have uncertainties, so how does one say they are (statistically) different without a test? We originally discussed differences based on non-overlapping fiducial limits, but a reviewer requested formal testing with correction for multiple comparisons How'd you address this request? Suggested papers to cite? $\endgroup$ –
  • Fiducial Inference in Machine Learning - Cross Validated
    I was looking at the Fiducial Inference page on wikipedia, which is an alternative to the traditional Frequentist and Bayesian standpoints Although it was out of favour in mainstream statistics for many years, there seems to have been a resurgence in interest in recent years (see for example Jan Hannig's recent publications on the subject )
  • Compare 90th percentiles of two samples (confidence interval, test)
    Interpret the fiducial distributions as probabilitiy distributions (this is an approximation, the fiducial distribution does not behave exactly like a probability distribution) and compute the probabilities for the joint probabilities of the two parameters percentiles to be inside the 2-d bins cells created by the grid
  • How to compute confidence interval from a confidence distribution
    From a statistical model I obtained a fiducial distribution that it's also a confidence distribution Saying, from a random variable X distributed as a Binomial, I obtained the fiducial distribution of the parameter p which is a Beta And I know that this fiducial distribution is also a confidence distribution
  • Terminology in interval estimation - Cross Validated
    (1) Confidence intervals (2) Posterior probability intervals (3) Fiducial intervals Is there some conventional term that encompasses these three sorts of intervals, but does not include prediction
  • How to interpret confidence interval of the difference in means in one . . .
    The fact that one set of interval bounds can come from methods based on either of two philosophically distinct paradigms leads to a really confusing situation--the results can be interpreted in two contradictory ways From the fiducial argument there is a 95% likelihood that a particular 95% fiducial interval will contain the true parameter value
  • Whats the difference between a confidence interval and a credible . . .
    Fisher extended the strategy of conditioning on the ancillary statistic to a general theory called Fiducial Inference (also called his greatest failure, cf Zabell, Stat Sci 1992), but it didn't become popular due to lack of generality and flexibility Fisher was trying to find a way different from both the classical statistics (of Neyman





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