The New S Language

Becker, Richard A.; Chambers, John M.; Wilks, Allan R.

doi:10.1201/9781351074988

Cited by 326 publications

(217 citation statements)

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“…As the variables were measured on considerably different scales, terms were centred by subtracting the variables mean value from each individual value and then rescaled by dividing each centred value by the overall standard deviation (Becker, Chambers, & Wilks, 1988). The log-transformed Gaussian proved to have the best fit and so was used in all the subsequent models.…”

Section: Statistical Modelmentioning

confidence: 99%

Decadal changes in habitat characteristics influence population trajectories of southern elephant seals

Hindell

Sumner

Bestley

et al. 2017

Global Change Biology

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Understanding divergent biological responses to climate change is important for predicting ecosystem level consequences. We use species habitat models to predict the winter foraging habitats of female southern elephant seals and investigate how changes in environmental variables within these habitats may be related to observed decreases in the Macquarie Island population. There were three main groups of seals that specialized in different ocean realms (the sub-Antarctic, the Ross Sea and the Victoria Land Coast). The physical and climate attributes (e.g. wind strength, sea surface height, ocean current strength) varied amongst the realms and also displayed different temporal trends over the last two to four decades. Most notably, sea ice extent increased on average in the Victoria Land realm while it decreased overall in the Ross Sea realm. Using a species distribution model relating mean residence times (time spent in each 50 × 50 km grid cell) to 9 climate and physical co-variates, we developed spatial predictions of residence time to identify the core regions used by the seals across the Southern Ocean from 120°E to 120°W. Population size at Macquarie Island was negatively correlated with ice concentration within the core habitat of seals using the Victoria Land Coast and the Ross Sea. Sea ice extent and concentration is predicted to continue to change in the Southern Ocean, having unknown consequences for the biota of the region. The proportion of Macquarie Island females (40%) utilizing the relatively stable sub-Antarctic region, may buffer this population against longer-term regional changes in habitat quality, but the Macquarie Island population has persistently decreased (-1.45% per annum) over seven decades indicating that environmental changes in the Antarctic are acting on the remaining 60% of the population to impose a long-term population decline in a top Southern Ocean predator.

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Section: Statistical Modelmentioning

confidence: 99%

Decadal changes in habitat characteristics influence population trajectories of southern elephant seals

Hindell

Sumner

Bestley

et al. 2017

Global Change Biology

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“…Tibshirani and Wang (2007) proposed an estimate of λ based on a pre-smoothed fit of a univariate time series using a lowess estimator (Becker et. al, 1988).…”

Section: Methodsmentioning

confidence: 99%

Estimating dynamic brain functional networks using multi-subject fMRI data

et al. 2018

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A common assumption in the study of brain functional connectivity is that the brain network is stationarity. However it is increasingly recognized that the brain organization is prone to variations across the scanning session, fueling the need for dynamic connectivity approaches. One of the main challenges in developing such approaches is that the frequency and change points for the brain organization are unknown, with these changes potentially occurring frequently during the scanning session. In order to provide greater power tso detect rapidly evolving connectivity changes, we propose a fully automated two-stage approach which pools information across multiple subjects to estimate change points in functional connectivity, and subsequently estimates the brain networks within each state phase lying between consecutive change points. The number and positioning of the change points are unknown and learned from the data in the first stage, by modeling a time-dependent connectivity metric under a fused lasso approach. In the second stage, the brain functional network for each state phase is inferred via sparse inverse covariance matrices. We compare the performance of the method with existing dynamic connectivity approaches via extensive simulation studies, and apply the proposed approach to a saccade block task fMRI data.

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“…When two notched box plots are superimposed by shifting them horizontally and the notches overlap, then it cannot be said, with a 95% confidence factor, that the medians do not come from the same distribution. [5,6] The double negative in the last sentence is not preciseIy the same as the positive. At the risk of oversimplification, the double negative means that the medians may come from the same distribution.…”

Section: Data Analysis Proceduresmentioning

confidence: 94%

“…The data was automatically transferred to ASCII files for data analysis. [5] This process was repeated 3 times…”

Section: Measurement Proceduresmentioning

confidence: 99%

A new method for measuring the shielding effectiveness of interconnections in shielding technologies: application to cellular phone gaskets for the housing

Haynes

Muniz²,

Smith³

Proceedings of Symposium on Electromagnetic Compatibility

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The New S Language

Cited by 326 publications

References 0 publications

Decadal changes in habitat characteristics influence population trajectories of southern elephant seals

Decadal changes in habitat characteristics influence population trajectories of southern elephant seals

Estimating dynamic brain functional networks using multi-subject fMRI data

A new method for measuring the shielding effectiveness of interconnections in shielding technologies: application to cellular phone gaskets for the housing

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