Silverman, B. W.: Density Estimation for Statistics and Data Analysis. Chapman &amp; Hall, London – New York 1986, 175 pp., £12.—

Läuter, H.

doi:10.1002/bimj.4710300745

Cited by 34 publications

(13 citation statements)

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“…We then took the slope from each lake and calculated the mean slope across all lakes and its 95% confidence interval to test for a statistically significant difference from zero using bootstrapping with 1000 iterations. Slope distributions were displayed using kernel density estimation (Läuter, 1988; Scott, 2015; Sheather & Jones, 1991). A positive mean slope and confidence interval that does not include zero indicated support for our hypothesis that earlier runoff corresponds with lower summer phytoplankton Chl‐ a .…”

Section: Methodsmentioning

confidence: 99%

Earlier winter/spring runoff and snowmelt during warmer winters lead to lower summer chlorophyll‐a in north temperate lakes

Hrycik

Isles

Adrian

et al. 2021

Global Change Biology

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Winter conditions, such as ice cover and snow accumulation, are changing rapidly at northern latitudes and can have important implications for lake processes. For example, snowmelt in the watershed—a defining feature of lake hydrology because it delivers a large portion of annual nutrient inputs—is becoming earlier. Consequently, earlier and a shorter duration of snowmelt are expected to affect annual phytoplankton biomass. To test this hypothesis, we developed an index of runoff timing based on the date when 50% of cumulative runoff between January 1 and May 31 had occurred. The runoff index was computed using stream discharge for inflows, outflows, or for flows from nearby streams for 41 lakes in Europe and North America. The runoff index was then compared with summer chlorophyll‐a (Chl‐a) concentration (a proxy for phytoplankton biomass) across 5–53 years for each lake. Earlier runoff generally corresponded to lower summer Chl‐a. Furthermore, years with earlier runoff also had lower winter/spring runoff magnitude, more protracted runoff, and earlier ice‐out. We examined several lake characteristics that may regulate the strength of the relationship between runoff timing and summer Chl‐a concentrations; however, our tested covariates had little effect on the relationship. Date of ice‐out was not clearly related to summer Chl‐a concentrations. Our results indicate that ongoing changes in winter conditions may have important consequences for summer phytoplankton biomass and production.

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Section: Methodsmentioning

confidence: 99%

Earlier winter/spring runoff and snowmelt during warmer winters lead to lower summer chlorophyll‐a in north temperate lakes

Hrycik

Isles

Adrian

et al. 2021

Global Change Biology

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“…The attribute data of the points included sociodemographic data for informants, and the categories of services (see Table 1). Maps showing the intensity of set points in space were then generated using ArcGIS 10.1 and its kernel density tool (Silverman 1986). The tool allows for the identification of areas on the map in which the density of points is high, or above a certain threshold.…”

Section: Methodsmentioning

confidence: 99%

Culture, Nature, and the Valuation of Ecosystem Services in Northern Namibia

Schnegg¹,

Rieprich²,

Pröpper³

2014

E&S

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Defining culture as shared knowledge, values, and practices, we introduce an anthropological concept of culture to the ecosystem-service debate. In doing so, we shift the focus from an analysis of culture as a residual category including recreational and aesthetic experiences to an analysis of processes that underlie the valuation of nature in general. The empirical analysis draws on ethnographic fieldwork conducted along the Okavango River in northern Namibia to demonstrate which landscape units local populations value for which service(s). Results show that subjects perceive many places as providing multiple services and that most of their valuations of ecosystem services are culturally shared. We attribute this finding to common experiences and modes of activities within the cultural groups, and to the public nature of the valuation process.

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“…For data that are Gaussian-distributed, thresholds on the likelihood of data modeled by a Gaussian probability distribution, or a mixture of Gaussians using Gaussian Mixture Models (GMM), can be used to identify novel or outlying examples (Chandola et al 2009). Similarly, kernel density estimators (KDE) estimate the probability density of a dataset by assigning individual kernels (e.g., Gaussian kernels) to each data point and summing over all the kernels (Silverman 1986). Dense regions where points are close together will contribute more to the density estimate than points in diffuse regions of the feature space, thus outliers can be identified using a threshold on the likelihood under the learned probability distribution (e.g., Desforges et al 1998;Latecki et al 2007;Ristic et al 2008;Laxhammar et al 2009;Schubert et al 2014).…”

Section: Related Workmentioning

confidence: 99%

Comparison of novelty detection methods for multispectral images in rover-based planetary exploration missions

Kerner

Wagstaff

Bue

et al. 2020

Data Min Knowl Disc

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Science teams for rover-based planetary exploration missions like the Mars Science Laboratory Curiosity rover have limited time for analyzing new data before making decisions about follow-up observations. There is a need for systems that can rapidly and intelligently extract information from planetary instrument datasets and focus attention on the most promising or novel observations. Several novelty detection methods have been explored in prior work for three-channel color images and non-image datasets, but few have considered multispectral or hyperspectral image datasets for the purpose of scientific discovery. We compared the performance of four novelty detection methods—Reed Xiaoli (RX) detectors, principal component analysis (PCA), autoencoders, and generative adversarial networks (GANs)—and the ability of each method to provide explanatory visualizations to help scientists understand and trust predictions made by the system. We show that pixel-wise RX and autoencoders trained with structural similarity (SSIM) loss can detect morphological novelties that are not detected by PCA, GANs, and mean squared error autoencoders, but that the latter methods are better suited for detecting spectral novelties—i.e., the best method for a given setting depends on the type of novelties that are sought. Additionally, we find that autoencoders provide the most useful explanatory visualizations for enabling users to understand and trust model detections, and that existing GAN approaches to novelty detection may be limited in this respect.

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Silverman, B. W.: Density Estimation for Statistics and Data Analysis. Chapman & Hall, London – New York 1986, 175 pp., £12.—

Cited by 34 publications

References 0 publications

Earlier winter/spring runoff and snowmelt during warmer winters lead to lower summer chlorophyll‐a in north temperate lakes

Earlier winter/spring runoff and snowmelt during warmer winters lead to lower summer chlorophyll‐a in north temperate lakes

Culture, Nature, and the Valuation of Ecosystem Services in Northern Namibia

Comparison of novelty detection methods for multispectral images in rover-based planetary exploration missions

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