Search results for "Normal Distribution"

An Empirical Evaluation of the Utility of Convex Hull and Standard Ellipse Areas for Assessing Population Niche Widths from Stable Isotope Data

2013

Stable isotope analyses are increasingly employed to characterise population niche widths. The convex hull area (TA) in a δ¹³C–δ¹⁵N biplot has been used as a measure of isotopic niche width, but concerns exist over its dependence on sample size and associated difficulties in among-population comparisons. Recently a more robust method was proposed for estimating and comparing isotopic niche widths using standard ellipse areas (SEA), but this approach has yet to be tested with empirical stable isotope data. The two methods measure different kind of isotopic niche areas, but both are now widely used to characterise isotopic niche widths of populations. We used simulated data and an extensive e…

The influence of temperature model assumptions on the prognosis accuracy of extinction risk

2000

Abstract For a species whose abundance is well-known to correlate on the degree of heat different temperature model assumptions may affect the prognosis accuracy of persistence. Likewise, year-to-year autocorrelations in weather fluctuations are known to decrease extinction risk. Thus, we investigated the grey bush cricket Platycleis albopunctata . For this species is known that growth and reproduction is mainly influenced by temperature. We developed a stochastic individual based model for the bush cricket. This day–degree model described the demographic growth of the species that depends on temperature. Daily temperatures were generated by five different methods: (i) temperatures were seq…

L1-Penalized Censored Gaussian Graphical Model

2018

Graphical lasso is one of the most used estimators for inferring genetic networks. Despite its diffusion, there are several fields in applied research where the limits of detection of modern measurement technologies make the use of this estimator theoretically unfounded, even when the assumption of a multivariate Gaussian distribution is satisfied. Typical examples are data generated by polymerase chain reactions and flow cytometer. The combination of censoring and high-dimensionality make inference of the underlying genetic networks from these data very challenging. In this article, we propose an $\ell_1$-penalized Gaussian graphical model for censored data and derive two EM-like algorithm…

Model selection for factorial Gaussian graphical models with an application to dynamic regulatory networks.

2016

Abstract Factorial Gaussian graphical Models (fGGMs) have recently been proposed for inferring dynamic gene regulatory networks from genomic high-throughput data. In the search for true regulatory relationships amongst the vast space of possible networks, these models allow the imposition of certain restrictions on the dynamic nature of these relationships, such as Markov dependencies of low order – some entries of the precision matrix are a priori zeros – or equal dependency strengths across time lags – some entries of the precision matrix are assumed to be equal. The precision matrix is then estimated by l 1-penalized maximum likelihood, imposing a further constraint on the absolute value…

Invited commentary to: ADAMTS13 deficiency is associated with abnormal distribution of von Willebrand factor multimers in patients with COVID-19 by T…

2021

Two-stage multi-Gaussian fitting of conduit artery photoplethysmography waveform during induced unilateral hemodynamic events.

2014

Photoplethysmography (PPG) is an optical technique with high diagnostic potential, yet clinical applications remain underdeveloped. Standardization of signal recording and quantification of waveform are essential prerequisites for broader clinical use. The aim of this study was to utilize a two-stage multi-Gaussian fitting technique in order to examine the parameters of conduit artery PPG waveform recorded during increasing the unilateral regional vascular resistance (RVR). This study was conducted on 14 young and healthy volunteers; various external compressions (ECs) were performed by inflating a tight cuff at 0, 40, 80, and 200 mmHg, while registering femoral PPG (wavelength 880 nm), dia…

Gaussian Mixture Models and Model Selection for [18F] Fluorodeoxyglucose Positron Emission Tomography Classification in Alzheimer’s Disease

2015

We present a method to discover discriminative brain metabolism patterns in [18F] fluorodeoxyglucose positron emission tomography (PET) scans, facilitating the clinical diagnosis of Alzheimer's disease. In the work, the term "pattern" stands for a certain brain region that characterizes a target group of patients and can be used for a classification as well as interpretation purposes. Thus, it can be understood as a so-called "region of interest (ROI)". In the literature, an ROI is often found by a given brain atlas that defines a number of brain regions, which corresponds to an anatomical approach. The present work introduces a semi-data-driven approach that is based on learning the charac…

Design of measurement-based correlation models for shadow fading

2010

This paper deals with the design of measurement-based correlation models for shadow fading. Based on the correlation model, we design a simulation model using the sumof-sinusoids (SOS) method to enable the simulation of spatial lognormal processes characterizing real-world shadow fading scenarios. The model parameters of the simulation model are computed by applying the L p -norm method (LPNM). This method facilitates an excellent fitting of the simulation model's autocorrelation function (ACF) to that of measured channels. Our study includes an evaluation of all important statistical quantities of the proposed measurement-based simulation model, such as the probability density function (PD…

Functional connectivity inference from fMRI data using multivariate information measures

2022

Abstract Shannon’s entropy or an extension of Shannon’s entropy can be used to quantify information transmission between or among variables. Mutual information is the pair-wise information that captures nonlinear relationships between variables. It is more robust than linear correlation methods. Beyond mutual information, two generalizations are defined for multivariate distributions: interaction information or co-information and total correlation or multi-mutual information. In comparison to mutual information, interaction information and total correlation are underutilized and poorly studied in applied neuroscience research. Quantifying information flow between brain regions is not explic…

A new Framework for the Spectral Information Decomposition of Multivariate Gaussian Processes

2021

: Different information-theoretic measures are available in the literature for the study of pairwise and higher-order interactions in multivariate dynamical systems. While these measures operate in the time domain, several physiological and non-physiological systems exhibit a rich oscillatory content that is typically analyzed in the frequency domain through spectral and cross-spectral approaches. For Gaussian systems, the relation between information and spectral measures has been established considering coupling and causality measures, but not for higher-order interactions. To fill this gap, in this work we introduce an information-theoretic framework in the frequency domain to quantify t…