Sentence examples for approximation to the distribution from inspiring English sources

As an application, we will derive an explicit error bound of Gaussian approximation to the distribution of a sum of independent and identically distributed Banach space-valued random variables based on a Lindeberg Lévy type limit theorem.

Further, it is shown that using the first three statistical moments, a good approximation to the distribution can be obtained.

With normal approximation to the distribution of the estimated SPK, two useful criteria for fuzzy hypothesis testing, critical value and fuzzy p-value, are developed to assess process yield based on SPK.

In the multivariate case, we provide a quasi-binomial approximation to the distribution of both the resubstitution and leave-one-out error estimators for LDA, under a common but otherwise arbitrary class covariance matrix, which is assumed to be known in the design of the LDA discriminant.

"A Saddlepoint approximation to the distribution of sum of i.n.i.d.n.i.d

Herein, we consider an approximation to the distribution of (S_n).

To create approximations to the distribution of Pr values we computed 214 samples from the stochastic map, after discarding a brief initial transient.

In particular, Wald-type confidence intervals were computed for parameter estimates, whilst significance tests were based on χ2 approximations to the distribution of the log likelihood ratio.

The total sample size for the study was 92, which is an adequate sample size because 30 or more gives a reasonable approximation [ 36] for using large sample approximations to the distribution of the test statistics that were used in our data analysis [ 37, 38].

The result is a different kind of approximation to the binomial distribution, called the Poisson distribution (after the French mathematician Siméon-Denis Poisson) or the law of small numbers.

The chapters cover four themes: identification and efficient estimation in econometrics, asymptotic approximations to the distributions of econometric estimators and tests, inference involving potentially nonstationary time series, such as processes that might have a unit autoregressive root, and nonparametric and semiparametric inference.