Sentence examples for nominal variance from inspiring English sources

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.

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).

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).

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.

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.

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

a This is the correlation between the variances of the two defined therapy groups (minor surgery and referral) at GP level b because we used nominal data the variance at the lowest level (episodes) is not determined but given by π/3 c calculated by intercept plus and minus 1.96 times the square root of the between practice variation and transformed back from a logit scale).

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.

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.

For fasting glucose, 27.0% of the total phenotypic variance (P-nominal = 0.023) was explained by the GxE of the ratio of AA/ EPA + DHA), whereas 13.1% of the variance was accounted for by additive genetic variance (Table  2, Additional file 1: Table S3).