Sentence examples for survival density from inspiring English sources

Let f(t) be the probability density survival function and F t) be the cumulative probability survival density for survival time, then the likelihood with exact and right censored observations is: left({displaystyle {prod}_{i=1}^mfleft {t}_iright)}right){left 1-F(T)right)}^{left 1-F

Note that the relation between the spike time survival density, G ¯ ϕ and the transition distribution, F ϕ, in Eq. (7) could also allow for an approximate maximum likelihood estimator (MLE), based on maximizing L MLE = ∑ n log ( g ϕ n − 1 ( i n ) ) = ∑ n log [ − ∂ t F α, β, γ ϕ n − 1 ( x th, t ) ] | t = i n, where the derivative has to be approximated by finite differences.

Warm anomalies have been linked to increased populations and virulence of pathogens [19] and the corollary, that cold anomalies may reduce survival, density and virulence of pathogens, has also been proposed [11].

In addition to the large increase in data, a major new feature is the ability to generate survival density plots.

The assumption of proportional hazards for Cox models was checked by plotting the log of the negative log of the survival density functions vs the log of survival time.

Comparing the morphological and functional traits of several invading species, Lamarque et al. (2011) found that growth rate was more linked to tree species invasiveness than other traits, such as seedling survival, density, biomass and seed germination.

A single time step represents a generation, which includes five events (Fig. 1): reproduction, density-dependent survival, density-independent survival, natural selection, and escape of cultured individuals.

Here, we mathematically detail the model given the default life cycle ordering of reproduction – escape – density-dependent survival – density-independent survival – selection.

In addition to vital rates such as survival, density-dependent regulation may apply to other aspects of a species' biology, such as growth, behaviour, incidence of disease and distribution [ 57, 62, 63].

These results indicate that seagrass fragmentation does not have an overriding influence on juvenile blue crab survival and density, and that crab cannibalism and seasonal changes in landscape structure may influence relationships between crab survival and seagrass habitat structure.

Let G ¯ ( x ) = 1 − G ( x ) and g(x)=d G x)/d x be the survival and density functions of a continuous random variable Y with baseline cdf G x).