Sentence examples for nominal variances from inspiring English sources

Such differences between observed and nominal variances can be interpreted as brought about by failures of some of the basic assumptions of the model.

He demonstrated that discrepancies between observed and nominal variances are conveyed by a hazard function of the waiting times that is not constant, but instead is a decreasing function of time inducing over-dispersion or an increasing function of time inducing under-dispersion.

Table 3 Device parameters of STT-RAM   Nominal Variance Transistor channel length(nm) 325%% Transistor channel width (nm) 96, 128, 160 5% Transistor threshold (RDF) 0.4 V σ VT =40 mV Rp (P) 2.25K Approximately 6% RAP (AP) 4.5K Approximately 6% MTJ initial angle 0 0.1π.

In this estimation, we assumed a quasibinomial distribution of error, allowing a larger variance than the nominal variance of a binomial distribution because of the overdispersion of maturity variables (McCullagh and Nelder 1989; R Development Core Team 2007).

Using a quasibinomial family allows the model to estimate a dispersion parameter which will scale the nominal variance to take into account departure from a true binomial error (McCullagh and Nelder 1989, p. 124 128).

This model was preferred over conventional Poisson regression because substantial over-dispersion on nominal Poisson variance was present, as indicated by the estimated value 9.8 and SE 3.4 of the dispersion parameter in the final negative binomial model.

Firstly, based on non-statistical grey mathematical theory, uncertainty information including nominal values, standard variances, and uncertainty matrix can be evaluated for elastic mechanical parameters of composites.

Demographic characteristics were investigated using the Chi-square test for independence (nominal variables) and analysis of variance (ANOVA) (continuous variables) followed up by Bonferroni post-hoc tests for group comparisons when adequate.

The nominal values and variance of the device parameters are listed in Table3.

The chi-square statistical test for nominal variables and one way analysis of variance for continuous variables were performed to assess whether there were significant differences among the groups stratified by sleep duration.

Open-loop simulations of a two-phase synthetic reservoir demonstrate that TE methods may significantly improve short-term risk measures such as expected return, standard deviation and conditional value-at-risk compared to nominal, robust and mean-variance optimization.