Is Human Height Bimodal?

Schilling, Mark F.; Watkins, Ann Vreeland; Watkins, William

doi:10.1198/00031300265

Cited by 113 publications

(85 citation statements)

References 17 publications

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“…The last fit, with w = 0.20, detected two components (in addition to a peak related to short GRBs) of approximately the same height and comparable standard deviations in a region of long GRBs. For these last two fits, the dispersion of a corresponding peak of a two-Gaussian is greater than the dispersion of both the components in the three-Gaussian, hence it gives a hint toward the bimodality of the GRBs (Schilling et al 2002). This is in agreement with a very high probability that the third group in a three-component model is a statistical fluctuation.…”

Section: Standard Normal Distributionssupporting

confidence: 73%

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Analysis ofFermigamma-ray burst duration distribution

Tarnopolski

2015

A&A

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Context. Two classes of gamma-ray bursts (GRBs), short and long, have been determined without any doubts, and are usually prescribed to different physical scenarios. A third class, intermediate in T 90 durations has been reported in the datasets of BATSE, Swift, RHESSI, and possibly BeppoSAX. The latest release of >1500 GRBs observed by Fermi gives an opportunity to further investigate the duration distribution. Aims. The aim of this paper is to investigate whether a third class is present in the log T 90 distribution, or whether it is described by a bimodal distribution. Methods. A standard χ 2 fitting of a mixture of Gaussians was applied to 25 histograms with different binnings. Results. Different binnings give various values of the fitting parameters, as well as the shape of the fitted curve. Among five statistically significant fits, none is trimodal. Conclusions. Locations of the Gaussian components are in agreement with previous works. However, a trimodal distribution, understood in the sense of having three distinct peaks, is not found for any binning. It is concluded that the duration distribution in the Fermi data is well described by a mixture of three log-normal distributions, but it is intrinsically bimodal, hence no third class is present in the T 90 data of Fermi. It is suggested that the log-normal fit may not be an adequate model.

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Section: Standard Normal Distributionssupporting

confidence: 73%

“…The fit for w = 0.26 does not fulfil this condition either, where the appropriate S (r) = 1.16 is taken from (Schilling et al 2002). The remaining three cases, although the shoulder is prominent, are also apparently bimodal.…”

Section: Discussionmentioning

confidence: 99%

Analysis ofFermigamma-ray burst duration distribution

Tarnopolski

2015

A&A

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“…The frequency distribution of foraging trip durations was bimodal, shown as two separate log-normal distributions of short and long trips (see later). The difference between the means of the distributions was greater than the sum of their standard deviations (Schilling et al 2002). The cut-off value separating short and long trips (6 h for experimental and 10 h for control birds) was obtained by calculating the minimal sum of the variances of both trip types given their log-normal distribution (Welcker et al 2009a).…”

Section: Foraging Effortmentioning

confidence: 99%

The effects of loggers on the foraging effort and chick-rearing ability of parent little auks

et al. 2011

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We studied the effects of loggers attached to chick-rearing little auks (Alle alle) on their daily time budget (proportion of time spent in the colony and at sea), foraging activity (duration and proportion of long and short foraging flights), chick provisioning rate and their growth and development on Spitsbergen. We found that experimental parent birds performed shorter but more frequent long foraging flights and reduced the frequency of short foraging flights. They spent more time at the colony and reduced chick provisioning rate compared to control birds. Nestlings reared by experimental parents weighed significantly less at their middle, peak and fledging age and departed colony later than chicks of control parents. Little auks depend on energy-rich copepods associated with cold Arctic waters and are expected to face the climate-induced worsening of the foraging conditions, which may have negative impact on their time/energy budget and survival. The study may help to determine the level of extra effort little auks need to invest to breed successfully.

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“…Using the analysis in [24], we can see that as long as the combined distribution for any two distributions is bimodal, Sd gain is able to separate the two distributions early in the tree construction process. Using two distributions of the same variance i.e.…”

Section: Detecting Clustered Anomalies Using Sd Gain Criterionmentioning

confidence: 99%

“…Using two distributions of the same variance i.e. σ 2 1 = σ 2 2 , with their respective means μ 1 and μ 2 , it is shown that the combined distribution can only be bimodal when |μ 2 − μ 1 | > 2σ [24]. In the case when σ 2 1 = σ 2 2 , the condition of bi-modality is |μ 2 − μ 1 | > S(r)(σ 1 + σ 2 ), where the ratio r = σ 2 1 /σ 2 2 and separation factor [24].…”

Section: Detecting Clustered Anomalies Using Sd Gain Criterionmentioning

confidence: 99%

On Detecting Clustered Anomalies Using SCiForest

Liu

Ting

Zhou

2010

Lecture Notes in Computer Science

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Abstract. Detecting local clustered anomalies is an intricate problem for many existing anomaly detection methods. Distance-based and density-based methods are inherently restricted by their basic assumptions-anomalies are either far from normal points or being sparse. Clustered anomalies are able to avoid detection since they defy these assumptions by being dense and, in many cases, in close proximity to normal instances. In this paper, without using any density or distance measure, we propose a new method called SCiForest to detect clustered anomalies. SCiForest separates clustered anomalies from normal points effectively even when clustered anomalies are very close to normal points. It maintains the ability of existing methods to detect scattered anomalies, and it has superior time and space complexities against existing distance-based and density-based methods.

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Is Human Height Bimodal?

Cited by 113 publications

References 17 publications

Analysis ofFermigamma-ray burst duration distribution

Analysis ofFermigamma-ray burst duration distribution

The effects of loggers on the foraging effort and chick-rearing ability of parent little auks

On Detecting Clustered Anomalies Using SCiForest

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