We develop a simple model where the prior knowledge is given by the probability of a gene-gene interaction based on two probability distributions for true and false interactions respectively.
In comparison to the estimates based on five probability distribution functions, LP III distribution shows the least value of Chi-square value for the return period up to 100 years and can be adopted for estimation of rainfall amounts at various probability levels.
The ratio of filled/empty chests is based on three probability distributions: the number of items per patch is either Poisson distributed (random distribution, 1 map, λ = 30), binomially distributed (even distribution, 2 maps, respectively. p = 0.25 and p = 0.4) or negative binomially distributed (very clumped distribution, 2 maps, respectively. k = 0.5; µ = 10 and k = 0.1; µ = 15).
Thus, the proposed curve modeling is based on two agents: probability distribution and nodes combination.
All analyses were performed with SPSS (version 14), and all tests of significance were based on two sided probability.
In the absence of agent interactions, the probability that a patient responds to a treatment based on two agents equals one minus the probability that he/she does not respond to either treatment: q ij = 1 − (1 − p i )(1 − p j ), where p i and p j are the response probabilities for each agent when used as a single agent.
This study employs the Tsallis entropy for deriving the rating curve, based on two simple constraints: (1) total probability and (2) mean discharge.
To do this, we model the connection degree of the individuals in the network as a probability distribution based on two parameters: μ and σ. μ represents the mean value at the peak of the probability distribution; σ represents the standard deviation.
Notes: Result from multivariate test Large number of decimal places have been given to illustrate similarity of probability values based on two methods.
Genes were selected to be included for transcriptional profile based on two criteria: a greater than 99% probability of being differentially expressed (P ≤ 0.01) and an expression level change of 2 fold or greater.
