Sentence examples for continuous exponential distribution from inspiring English sources
For example, by exponentiating the cdf of the continuous exponential distribution Gupta and Kundu (1999) derived generalized exponential distribution having pdf, cdf and sf {f}_x x)=alpha lambda {left 1-{e}^{left 1-{e}right)}^{alpha -1}{e}^{-lambda x},kern0.24em x>0,alpha >0,lambda >0.
It is thought of as the discrete analogue of the continuous exponential distribution (Johnson et al. [2005]).
Sato et al. (1999) proposed discrete exponential distribution having similar looking structure starting with the continuous exponential distribution having pdf f(x)=lambda {e}^{-lambda x},kern0.24em x>0,alpha >0,lambda >0.
Hence, the appropriate probability density function is a continuous exponential distribution of the form f(t)=λ e−λ t where λ is the single parameter that governs the rate of loss.
Di is assigned randomly to these individuals from a continuous exponential probability distribution with hazard rate rd, leading to a declining incidence of recurrence with increasing time from initial treatment at the population level [ 38].
Bacterial abundance was assumed to be the continuous variable with exponential distribution dependent on the set of categorical predictors: absence of the analyzed genes (iroN, iutA, iha, ireA, chuA and hlyA); group of patients; and the site of material origin.
For example, loss may follow a continuous exponential or a Weibull distribution, with loss decreasing over time after a threshold is exceeded, while recovery may follow a normal distribution that incorporates a lag-phase.
Time until next reaction a sum x e − a sum x τ is the density function for a continuous random variable with an exponential distribution.
The exponential distribution is a continuous random variable with the probability density function: (3.80).
In an attempt to understand the events shaping the distribution of gene duplications in the apple, the fit of the distribution was evaluated to a mixture of densities involving an exponential distribution representing the continuous mode of small-scale duplications and several normal distributions representing putative large-scale duplication events.
An alternative assumption would be to assume a continuous-time Markov process, implying an exponential distribution of time of transition within the interval, but in intervals of 2 years, the difference between both assumptions is small [ 26].
