Violin Plots: A Box Plot-Density Trace Synergism

Hintze, Jerry L.; Nelson, Ray D.

doi:10.2307/2685478

Cited by 422 publications

(251 citation statements)

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“…Adult emergence data were visually examined with violin plots (Fig. 1), a combination of smoothed density plots and box plots (Hintze and Nelson 1998). Linear models for continuous maize and generalized linear models for first-year maize were then fitted to factors that could potentially influence the total number of emerged beetles, such as 'location', 'study year' and their interaction.…”

Section: Assessment Of Emergence Of Diabrotica V Virgifera Adultsmentioning

confidence: 99%

Generational growth rate estimates of Diabrotica virgifera virgifera populations (Coleoptera: Chrysomelidae)

et al. 2010

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Modelling population dynamics of the maize pest Diabrotica virgifera virgifera LeConte (western corn rootworm; Coleoptera: Chrysomelidae) requires knowledge on the growth rate (=net reproductive rate) of the species. We investigated the generational (=annual) growth rate of D. v. virgifera in isolated maize fields in southern Hungary and eastern Croatia over several years. The population densities of D. v. virgifera were assessed by absolute counts of emerging adults in 90 gauze cages per study field. Emergence ranged from 1.3 to 30.7 adults per m 2 in continuous maize field sections, and from 0.3 to 5.1 adults per m 2 in adjacent first-year maize sections. The annual growth rates of D. v. virgifera ranged from 0.5 to 13, and averaged in close to 4. These experimentally assessed growth rates could complement growth estimates in population dynamic models, particularly those for forecasting the population growth to economic thresholds or for estimating population build-ups after new introductions of this alien species in Europe. As an example, the determined growth rate was used to estimate that the first documented successful introduction of this species into Europe occurred between 1979 and 1984, which is 8-13 years before the detection of this species and its larval damage in maize fields near Belgrade, Serbia, in 1992.

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Section: Assessment Of Emergence Of Diabrotica V Virgifera Adultsmentioning

confidence: 99%

Generational growth rate estimates of Diabrotica virgifera virgifera populations (Coleoptera: Chrysomelidae)

et al. 2010

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“…The dots represent the median of 1000 posterior means. The violins around the dots are density estimates for the distribution of the 1000 posterior means, with the extreme 5% truncated (see alsoHintze & Nelson, 1998). The horizontal lines represent the true parameter values.…”

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confidence: 99%

Cognitive model decomposition of the BART: Assessment and application

Ravenzwaaij

Dutilh

Wagenmakers

2011

Journal of Mathematical Psychology

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“…Thus, the AIC is intended to facilitate model comparisons from the same data set and aids in the selection of optimal models, with lower AIC values indicating a better fitting model (Akaike, 1973(Akaike, , 1974. The relative performance of the models in the six different TWI parameter-groups listed above (i.e., source data, TI form, cell size, slope algorithm, flow direction algorithm and smoothing) were evaluated by two methods: (i) comparing the mean, median and overall probability distribution of AIC values via violin plots (see Hintze and Nelson, 1998 for a detailed description of these plots) and (ii) by pairwise comparison of TWIs that share the exact same parameter values in all respects except for, of course, the particular TWI parameter in question (see Table 3 for an example).…”

Section: Mixed Effects Modelingmentioning

confidence: 99%

Evaluating topographic wetness indices across central New York agricultural landscapes

Buchanan

Fleming

Schneider

et al. 2014

Hydrol. Earth Syst. Sci.

107

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Abstract. Accurately predicting soil moisture patterns in the landscape is a persistent challenge. In humid regions, topographic wetness indices (TWIs) are widely used to approximate relative soil moisture patterns. However, there are many ways to calculate TWIs and very few field studies have evaluated the different approaches -especially in the US. We calculated TWIs using over 400 unique formulations that considered different digital elevation model (DEM) resolutions (cell size), vertical precision of DEM, flow direction and slope algorithms, smoothing via low-pass filtering, and the inclusion of relevant soil properties. We correlated each TWI with observed patterns of soil moisture at five agricultural fields in central NY, USA, with each field visited five to eight times between August and November 2012. Using a mixed effects modeling approach, we were able to identify optimal TWI formulations applicable to moderate relief agricultural settings that may provide guidance for practitioners and future studies. Overall, TWIs were moderately well correlated with observed soil moisture patterns; in the best case the relationship between TWI and soil moisture had an average R 2 and Spearman correlation value of 0.61 and 0.78, respectively. In all cases, fine-scale (3 m) lidar-derived DEMs worked better than USGS 10 m DEMs and, in general, including soil properties improved correlations.

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Violin Plots: A Box Plot-Density Trace Synergism

Cited by 422 publications

References 0 publications

Generational growth rate estimates of Diabrotica virgifera virgifera populations (Coleoptera: Chrysomelidae)

Generational growth rate estimates of Diabrotica virgifera virgifera populations (Coleoptera: Chrysomelidae)

Cognitive model decomposition of the BART: Assessment and application

Evaluating topographic wetness indices across central New York agricultural landscapes

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