The distribution of the data suggested a lognormal distribution
of the LOAEL/NOAEL ratio.
Note: BMD, Benchmark Dose; BMDL, Benchmark Dose Lower Confidence Limit; BMDU, Benchmark Dose Upper Confidence Limit; BW, Body Weight; ED50, Effective Dose for a 50% response; LOAEL, Lowest Observed Adverse Effect Level; NOAEL, No Observed Adverse Effect Level; POD, Point of Departure; P50, median of the distribution = Geometric mean of lognormal distribution
; P95/P50, ratio between the 95th percentile and the median of the distribution = [(Geometric standard deviation of lognormal distribution
).sup.1.6449]; RfD, Reference Dose; SD, Standard Deviation; TD, Toxicodynamic; TK, Toxicokinetic; [UF.sub.L], Uncertainty Factor for LOAEL-to-NOAEL.
It was found that lognormal distribution
has the highest average acceptance rates; that is, 14/16 = 87.5%.
We proposed three new generalized p values for testing the hypotheses of (1) one population variance, (2) the difference between two population variances, and (3) the ratio of population variances of lognormal distributions
when the coefficients of variation are known.
Mean Lognormal Lognormal value COV [lambda] [zeta] Direction factor 0.8 0.2 -0.24275 0.198042 [S.sup.2.sub.d] Seasonal factor 0.65 0.3 -0.47387 0.29356 [S.sup.2.sub.s] Factor 3.6 0.15 1.269809 0.149166 [S.sup.2.sub.b] Elasticity 200 0.2 5.278707 0.198042 modulus E Table 10: Effect of climate change to changes in reliability Present Future Increased condition prediction percentage Extreme temperature ([degrees]C) 41.9 44.7~46.9 6.7~11.9 Extreme wind speed (m/s) 38.35 39.37~40.17 2.7~4.7 Failure probability Monte Carlo simulation 0.0343 0.0484~0.0591 41.1~72.3 First-order estimation 0.00504 0.01004~0.01455 99.2~188.9 Numerical integration 0.0211 0.0325~0.0409 54.0~93.8 Other effects Correlation ([rho] = 0.1) 0.034 0.0486~0.0588 42.9~72.9 Lognormal distribution
0.016 0.0251~0.032 56.9~100
For the occupancy schedules, the lognormal distribution
was used with Equation 3.
For soil parameters, which show typically a large scatterings (it means those with value of coefficient of variation CoV = S/[bar.X] > 0,3) the lognormal distribution
is preferable (Pohl 2011).
In our interpretation the two lognormal distributions
in the mix represent investors' view about two possible outcomes in the economy.
FMMs used here were composed of distributions drawn from five commonly used non mixture channel models, namely Rayleigh, Nakagami, Rice, Weibull and Lognormal distributions
. The component distributions of FMMs were chosen based on the wide usage in channel modeling literature.
The quantile-quantile (Q-Q) and probability plots were respectively used to test whether our study data follows the exponential and lognormal distributions
. The Kaplan-Meier method was used for the survival analyses.