ライフサイエンスコーパス: Poisson process

1 tributed and that they arrive according to a Poisson process.

2 d, is not distinguishable from a homogeneous Poisson process.

3 n successive ants returning to the nest is a Poisson process.

4 rons were less variable than expected from a Poisson process.

5 able signal: noise ratio than predicted by a Poisson process.

6 s (10-55 ms) more often than expected from a Poisson process.

7 ry process, rather than as a highly variable Poisson process.

8 for the 95% confidence limits expected for a Poisson process.

9 aced onto a phylogenetic tree according to a Poisson process.

10 vary across lineages according to a compound Poisson process.

11 described adequately by a simple stochastic Poisson process.

12 ribution or if burst arrival deviates from a Poisson process.

13 ibuted in time and thus well approximated by Poisson processes.

14 Standard results for Poisson processes allow key computations to be decoupled

15 complexes that are randomly distributed as a Poisson process among the population of granules.

16 Core teams form by a Poisson process and produce a Poisson distribution of te

17 ws nodes to arrive in batches according to a Poisson process and to form hyperedges with existing bat

18 the non-mutated positions, according to the Poisson process and/or the Taylor series.

19 ndomly within a sequence, then they follow a Poisson process, and a histogram of the number of observ

20 ow contrasts was greater than predicted by a Poisson process, and at high contrasts the responses wer

21 e count variability was lower than that of a Poisson process at all three stages but increased at eac

22 embles were well described as rate-modulated Poisson processes but with very high precision (approxim

23 eling the sampling times as an inhomogeneous Poisson process dependent on effective population size.

24 ata on activity distributions to ensure that Poisson processes do not distort the underlying LN distr

25 Inputs were Poisson process-driven excitatory and inhibitory synapti

26 s for bursty activity, and a non-homogeneous Poisson process for longer inactivity between bursts.

27 Although the fractal-Gaussian-rate Poisson process has not been proven to have better agree

28 e spike generation process was modelled as a Poisson process in which depolarizing events summate and

29 y visual cortex are well fit by a mixture of Poisson processes; in this special case, our computation

30 The fractal-Gaussian-rate Poisson process is compared and contrasted with previous

31 gs of the concerted changes closely follow a Poisson process model, and the sound transition networks

32 by mutational types is closely connected to Poisson process models of crystallization, which we exte

33 nalysis of SCR events, which do not follow a Poisson process observed in other eukaryotic cells.

34 uch responses was smaller than expected from Poisson processes, often reaching the theoretical minimu

35 s, but it has a global characterization as a Poisson process on the phylogeny.

36 t were not spatial random (i.e., homogeneous Poisson process) or regular but, instead, exhibited stro

37 ving rise to independent mutant gametes in a Poisson process, or before meiosis, giving rise to multi

38 ently probabilistic, and can be modeled as a Poisson process over short time scales.

39 he data) is incorrect, and (ii) the compound Poisson process prior model (which describes the prior d

40 d bacterial ssu rRNA's are consistent with a Poisson process since last common ancestor.

41 Emergency studies were modeled as a Poisson process; slots were reserved such that rate of r

42 We propose a cascading nonhomogeneous Poisson process that explicitly integrates these periodi

43 l spike trains are approximately independent Poisson processes, that correlations among them can be l

44 meaningfully compared to expectations from a Poisson process, the test does not permit calculations o

45 dels of molecular evolution, including other Poisson processes, the fractal renewal process, a Levy-s

46 And, by using the Poisson process theory and a continuity technique, the h

47 e distribution of the model by employing the Poisson process theory and the characteristic equation.

48 The Poisson process theory is used to describe the arrival p

49 pisodic models such as the doubly stochastic Poisson process, this model accounts for the large varia

50 We use nonhomogeneous Poisson processes to model the acquisition of parasites,

51 ions consistent with a fractal-Gaussian-rate Poisson process, which assumes common descent without as

52 king activity is modeled as an inhomogeneous Poisson process whose instantaneous rate is a function o

53 d a model in which spikes are generated by a Poisson process whose rate is the product of a drive tha