Skew‐Normal Family of Distributions

Azzalini, Adelchi

doi:10.1002/0471667196.ess3215

Cited by 11 publications

(5 citation statements)

References 14 publications

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“…The average was then computed using only the values of the three remaining replicates and was used as a representative value. Next, for each treatment, all representative siRNA values were converted into P values, using the SN package (59) for R platform to fit the skewed normal distribution. Finally, for each treatment, the 400 most extreme P values (containing a mix of the lowest and the highest values) were selected and used in the secondary screen with the dual luciferase reporter assay.…”

Section: Statistical Analysis Of Primary and Secondary Sirna Library ...mentioning

confidence: 99%

Interplay Between the Oxidoreductase PDIA6 and microRNA-322 Controls the Response to Disrupted Endoplasmic Reticulum Calcium Homeostasis

et al. 2014

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The disruption of the energy or nutrient balance triggers endoplasmic reticulum (ER) stress, a process that mobilizes various strategies, collectively called the unfolded protein response (UPR), which reestablish homeostasis of the ER and cell. Activation of the UPR stress sensor IRE1α (inositol-requiring enzyme 1α) stimulates its endoribonuclease activity, leading to the generation of the mRNA encoding the transcription factor XBP1 (X-box binding protein 1), which regulates the transcription of genes encoding factors involved in controlling the quality and folding of proteins. We found that the activity of IRE1α was regulated by the ER oxidoreductase PDIA6 (protein disulfide isomerase A6) and the microRNA miR-322 in response to disruption of ER Ca2+ homeostasis. PDIA6 interacted with IRE1α and enhanced IRE1α activity as monitored by phosphorylation of IRE1α and XBP1 mRNA splicing, but PDIA6 did not substantially affect the activity of other pathways that mediate responses to ER stress. ER Ca2+ depletion and activation of store operated Ca2+ entry reduced the abundance of the microRNA miR-322, which increased PDIA6 mRNA stability and consequently IRE1α activity during the ER stress response. In vivo experiments with mice and worms showed that the induction of ER stress correlated with decreased miR-322 abundance, increased PDIA6 mRNA abundance, or both. Together these findings demonstrated that ER Ca2+, PDIA6, IRE1α, and miR-322 function in a dynamic feedback loop modulating the UPR under conditions of disrupted ER Ca2+ homeostasis.

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Section: Statistical Analysis Of Primary and Secondary Sirna Library ...mentioning

confidence: 99%

Interplay Between the Oxidoreductase PDIA6 and microRNA-322 Controls the Response to Disrupted Endoplasmic Reticulum Calcium Homeostasis

et al. 2014

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“…The variables in the model in Equation (9) are selected using a BIC procedure similar to that used for the TDD model. The parameters are estimated using maximum likelihood estimation with the R package sn (Azzalini 2006). Figure 4 shows that the skew-t distribution for the errors is a much better fit to the 2002 training data than the normal distribution for the errors is.…”

Section: Bivariate Skew-t Modelmentioning

confidence: 99%

Powering Up With Space-Time Wind Forecasting

Hering¹,

Genton²

2010

Journal of the American Statistical Association

145

154

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The technology to harvest electricity from wind energy is now advanced enough to make entire cities powered by it a reality. High-quality short-term forecasts of wind speed are vital to making this a more reliable energy source. Gneiting et al. (2006) have introduced a model for the average wind speed two hours ahead based on both spatial and temporal information. The forecasts produced by this model are accurate, and subject to accuracy, the predictive distribution is sharp, i.e., highly concentrated around its center. However, this model is split into nonunique regimes based on the wind direction at an off-site location. This paper both generalizes and improves upon this model by treating wind direction as a circular variable and including it in the model. It is robust in many experiments, such as predicting at new locations. We compare this with the more common approach of modeling wind speeds and directions in the Cartesian space and use a skew-t distribution for the errors. The quality of the predictions from all of these models can be more realistically assessed with a loss measure that depends upon the power curve relating wind speed to power output. This proposed loss measure yields more insight into the true value of each model's predictions.

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“…For each population, the last Kaplan-Meier survival estimate, i.e., only one survivor in the jar or when the jar was terminated was plotted as a function of incubation temperature. The distributions of survival data were clearly asymmetrical, with higher values toward higher temperatures, and the skew-normal (SN) distribution was fitted to the survival data to account for the asymmetry (R package sn; Azzalini, 2016). The univariate SN density function of a random variable z is defined by…”

Section: Analyses: Survivalmentioning

confidence: 99%