Cumulative probability distribution

The cumulative probability distribution of fragments larger than length / is obtained from... 

Figure 19.8.6. A continuous cumulative probability distribution function.

Fig. 16.2 Cumulative probability distributions of Metalaxyl residue at 150, 300 and 500cm soil depths, simulated on the basis of Western Australian coastal sandy soil conditions. The diagram shows that the cumulative probabilities are high for Metalaxyl to reach the three soil depths at significant residue fractions (% applied)...

The z-scores are then transformed into scores between 0 and 1 by calculating the cumulative probability distribution for each score under the assumption of a normal distribution, which yields the final continuity and discontinuity scores ... 

In Fig. 9, we plot the cumulative probability distribution for finding water molecules in a cluster of given size for both the membranes at k = 4.4 to 12.8 using all three cut-off distances. Two important asymptotes can be considered in this figure. An aqueous domain that is poorly connected will be composed of many small clusters. Therefore, the cumulative probability will quickly rise to 1.0, indicating that all water molecules are in small clusters. The... 

Figure 5.17 Cumulative probability distribution for the occurrence of the nucleation coordinates of Fig. 5.16 in electrode segments along one of the coordinates, or y, respectively [5.22].

Probability Density Function and Cumulative Probability Distribution... 

Leff model). For quantal responses it reflects the cumulative probability distribution. 

B, The cumulated ratios (bars) and the estimated cumulative probability distribution (curve). (The data were computer generated for the purpose of illustration.)... 

Median values estimated so that F(rmed) 1/2, where F — empirical cumulative probability distribution function of r. Table 2 shows that mean and median values of galactocentric offsets of SNIb/c are very close to ones of GRBs. 

The relation shown in Fig. 6.7a is called the cumulative probability distribution. It is... 

If we have a set of data which are supposed to be normally distributed, we can construct cumulative probability distribution and plot this on nonnal probabilty paper. The result may be as in Fig. 6.8. 

As you might expect, the most probable outcome is 2 actives (probability 0.375) and the least probable outcomes are 0 and 4 actives (each with a probability of 0.0625). We can use the cumulative probability distribution to answer other probability questions of interest. For example, what is the probability of observing 3 or fewer actives This probability is denoted as P(A < 3) = 0.9375. We can use the complement rule from Section 6.2 to calculate the probability of observing 2 or more actives, P(X > 2), as ... 

Figure 3. Simulated cumulative probability distributions showing the effect of weather (as a function on depth) and application timing on the leaching of aldicarb residues.

Journel(7-9) provides a means for generating the desired mappings in situations such as the example site which are free from any undue assumptions regarding the distributional form of concentrations within blocks. This approach simply transforms the data into the sample cumulative probability distribution. This nonparametric geostatistical approach is sometimes called "indicator kriging."... 

Hartge et al. (1988) measured radial solids concentrations and probability density and cumulative probability distribution of ash particle in a 400 mm i.d. and 8 m high circulating fluidized bed, the results of which are shown in Figure 4-22. It can be found from comparison of data for the same... 

Construct cumulative probability distributions of duration by counting the fraction of duration with values less than or equal to the corresponding time points. This probability distribution... 

Fig. 4. Lifetime anaiysis of cARI-Haio-TMR and cARf-YFP. (a) Cumuiative probabiiity distributions of cARt-TMR (c/rc/e) and cARt -YFP (squar. Soiid iines represent the fitting of data to a singie or sum of exponentiai functions. The time constant of cARt -Haio-TMR, x = 11 s, represents the photobieaching time constant of TMR because cARt exists stabiy on the membrane. cARt -YFP had two time constants, x, = 0.52 s (86%) and x = 2.2 s (14%). This lifetime complexity for cARt -YFP may be due to YFP blinking. Semilogarithmic plots of cumulative probability distributions of cARI -YFP (b) and cARI-Haio-TMR (c), indicating multiple constants and single constant photobieaching time-lines, respectively. The semilogarithmic representation facilitates to discriminate the heterogeneity of lifetimes, (d) Lifetimes of cARI -Haio-TMR, PTEN-Halo-TMR, and Cy3-cAMP.

The information in Table I was reapportioned into the normalized cumulative probability distribution functions (PDF) shown in Figures 2 and 3 for kraft and MW lignin, respectively. The P and H substitutents were reorganized as either P-position terminal substituents or interunit linkages to facilitate probabilistic construction of representative lignin oligomers, as follows. 

Figure 1. Cumulative Probability Distribution Functions for Lignin Molecular Weight.

The scatter angle data are given in the form of a probability distribution. To simulate this, the standard statistical approach is to sample from a cumulative probability distribution. The probability of a neutron being scattered through an angle cos p is pdfi, so that in general it is necessary to solve the following equation for p,... 

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