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Gaussian distribution factors

The nickel concentration at ground level can then be estimated by using Eq. (4.16). The horizontal Gaussian distribution factor is 0 because the nickel... [Pg.372]

Multiple linear regression is strictly a parametric supervised learning technique. A parametric technique is one which assumes that the variables conform to some distribution (often the Gaussian distribution) the properties of the distribution are assumed in the underlying statistical method. A non-parametric technique does not rely upon the assumption of any particular distribution. A supervised learning method is one which uses information about the dependent variable to derive the model. An unsupervised learning method does not. Thus cluster analysis, principal components analysis and factor analysis are all examples of unsupervised learning techniques. [Pg.719]

Given the factors which influence the design of the stack, it is logical to proceed with the question of relating these factors to stack performance. It has already been proposed that a Gaussian distribution of pollutant... [Pg.294]

Just for fun, let s look at the distribution of the absorbances in each factor. Figure 59, contains histograms of the absorbances in the first 8 factors for the first training set. If a factor is purely a noise factor, it s absorbances should follow a gaussian distribution. The absorbances of the first 4 factors do appear to deviate significantly horn a gaussian distribution. Notice that, since our data... [Pg.120]

Figure 59. Histogram plots of the distributions of the absorbances of the first 8 factors of the training set, Al. A plot of an ideal gaussian distribution is superimposed on each histogram. Figure 59. Histogram plots of the distributions of the absorbances of the first 8 factors of the training set, Al. A plot of an ideal gaussian distribution is superimposed on each histogram.
Fig. 13. Calculated 2H solid echo spectra for log-Gaussian distributions of correlation times of different widths. Note the differences of the line shapes for fully relaxed and partially relaxed spectra. The centre of the distribution of correlation times is given as a normalized exchange rate a0 = 1/3tc. For deuterons in aliphatic C—H bonds the conversion factor is approximately 4.10s sec-1... Fig. 13. Calculated 2H solid echo spectra for log-Gaussian distributions of correlation times of different widths. Note the differences of the line shapes for fully relaxed and partially relaxed spectra. The centre of the distribution of correlation times is given as a normalized exchange rate a0 = 1/3tc. For deuterons in aliphatic C—H bonds the conversion factor is approximately 4.10s sec-1...
For a normal (Gaussian) error distribution, the RMSE is by a factor of Jl larger than the mean absolute error, also denoted as mean unsigned error. The error distribution of log Sw prediction methods appears to be somewhat less inhomogeneous than a Gaussian distribution and typically leads to a ratio of RMSE/mean absolute error... [Pg.308]

Each oil-dispersant combination shows a unique threshold or onset of dispersion [589]. A statistic analysis showed that the principal factors involved are the oil composition, dispersant formulation, sea surface turbulence, and dispersant quantity [588]. The composition of the oil is very important. The effectiveness of the dispersant formulation correlates strongly with the amount of the saturate components in the oil. The other components of the oil (i.e., asphaltenes, resins, or polar substances and aromatic fractions) show a negative correlation with the dispersant effectiveness. The viscosity of the oil is determined by the composition of the oil. Therefore viscosity and composition are responsible for the effectiveness of a dispersant. The dispersant composition is significant and interacts with the oil composition. Sea turbulence strongly affects dispersant effectiveness. The effectiveness rises with increasing turbulence to a maximal value. The effectiveness for commercial dispersants is a Gaussian distribution around a certain salinity value. [Pg.305]

In reality, the queue size n and waiting time (w) do not behave as a zero-infinity step function at p = 1. Also at lower utilization factors (p < 1) queues are formed. This queuing is caused by the fact that when analysis times and arrival times are distributed around a mean value, incidently a new sample may arrive before the previous analysis is finished. Moreover, the queue length behaves as a time series which fluctuates about a mean value with a certain standard deviation. For instance, the average lengths of the queues formed in a particular laboratory for spectroscopic analysis by IR, H NMR, MS and C NMR are respectively 12, 39, 14 and 17 samples and the sample queues are Gaussian distributed (see Fig. 42.3). This is caused by the fluctuations in both the arrivals of the samples and the analysis times. [Pg.611]

If U0 and U1 were the functions of a sufficient number of identically distributed random variables, then AU would be Gaussian distributed, which is a consequence of the central limit theorem. In practice, the probability distribution Pq (AU) deviates somewhat from the ideal Gaussian case, but still has a Gaussian-like shape. The integrand in (2.12), which is obtained by multiplying this probability distribution by the Boltzmann factor exp (-[3AU), is shifted to the left, as shown in Fig. 2.1. This indicates that the value of the integral in (2.12) depends on the low-energy tail of the distribution - see Fig. 2.1. [Pg.37]

The form factor term, P(q), contains information on the distribution of segments within a single dendrimer. Models can be used to fit the scattering from various types of particles, common ones being a Zimm function which describes scattering from a collection of units with a Gaussian distribution (equation (3a)), a... [Pg.259]

The Pearson VII model contains four adjustable parameters and is particularly well suited for the curve fitting of large spectral windows containing numerous spectral features. The adjustable parameters a, p, q and v° correspond to the amplitude, line width, shape factor and band center respectively. As q —the band reduces to a Lorenzian distribution and as q approaches ca. 50, a more-or-less Gaussian distribution is obtained. If there are b bands in a data set and... [Pg.174]

Investigation of the multivariate Gaussian distribution and the dipole moments of perturbed chains expansion factors for perturbed chains. [Pg.47]

The Gaussian distribution of h can be considered as frozen for this consideration. One factor h2 is already contained in eq. (5.20), which gives, after the replacement of the subscript V" by "e , the contribution of a special dumb-bell with momentary end-to-end distance h. The Maxwell-constant of a solution of an assembly of elastic dumb-bells consequently reads ... [Pg.269]


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