frequentist statistics造句
例句與造句
- (In some instances, frequentist statistics can work around this problem.
- Despite growth of Bayesian research, most undergraduate teaching is still based on frequentist statistics.
- However, some elements of frequentist statistics, such as statistical decision theory, do incorporate utility functions.
- Frequentist statistics, the more popular robust, with the posterior distribution less sensitive to the more flexible hierarchical priors.
- Those who promote Bayesian inference view " frequentist statistics " as an approach to statistical inference that recognises only physical probabilities.
- It's difficult to find frequentist statistics in a sentence. 用frequentist statistics造句挺難的
- After the 1920s, " inverse probability " was largely supplanted by a collection of methods that came to be called frequentist statistics.
- For instance, in frequentist statistics, likelihood ratios are computed against null models that may or may not be part of some hypothesis.
- After 1968, Basu began writing polemical essays, which provided paradoxes to frequentist statistics, and which produced great discussion in statistical journals and at statistical meetings.
- For example, confidence intervals and prediction intervals in frequentist statistics when constructed from a normal distribution with unknown mean and variance are constructed using a Student's t-distribution.
- Objective prior distributions may also be derived from other principles, such as information or coding theory ( see e . g . minimum description length ) or frequentist statistics ( see frequentist matching ).
- Compare this to the approach in frequentist statistics, where a single estimate of the parameters, e . g . a maximum likelihood estimate, would be computed, and this value plugged in.
- While frequentist statistics remains strong ( as seen by the fact that most undergraduate teaching is still based on it ), Bayesian methods are widely accepted and used, e . g ., in the field of machine learning.
- There are other methods of estimation that minimize the posterior " risk " ( expected-posterior loss ) with respect to a loss function, and these are of interest to statistical decision theory using the sampling distribution ( " frequentist statistics " ).
- Credible intervals are analogous to confidence intervals in frequentist statistics, although they differ on a philosophical basis; Bayesian intervals treat their bounds as fixed and the estimated parameter as a random variable, whereas frequentist confidence intervals treat their bounds as random variables and the parameter as a fixed value.
- By comparison, prediction in frequentist statistics often involves finding an optimum point estimate of the parameter ( s ) e . g ., by maximum likelihood or maximum a posteriori estimation ( MAP ) and then plugging this estimate into the formula for the distribution of a data point.
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