Search results for " statistics"
showing 10 items of 1891 documents
Anomalous transport effects on switching currents of graphene-based Josephson junctions
2017
We explore the effect of noise on the ballistic graphene-based small Josephson junctions in the framework of the resistively and capacitively shunted model. We use the non-sinusoidal current-phase relation specific for graphene layers partially covered by superconducting electrodes. The noise induced escapes from the metastable states, when the external bias current is ramped, give the switching current distribution, i.e. the probability distribution of the passages to finite voltage from the superconducting state as a function of the bias current, that is the information more promptly available in the experiments. We consider a noise source that is a mixture of two different types of proce…
Analyzing big datasets of genomic sequences: fast and scalable collection of k-mer statistics
2019
Abstract Background Distributed approaches based on the MapReduce programming paradigm have started to be proposed in the Bioinformatics domain, due to the large amount of data produced by the next-generation sequencing techniques. However, the use of MapReduce and related Big Data technologies and frameworks (e.g., Apache Hadoop and Spark) does not necessarily produce satisfactory results, in terms of both efficiency and effectiveness. We discuss how the development of distributed and Big Data management technologies has affected the analysis of large datasets of biological sequences. Moreover, we show how the choice of different parameter configurations and the careful engineering of the …
Data Augmentation Approach in Bayesian Modelling of Presence-only Data
2011
Abstract Ecologists are interested in prediction of potential distribution of species in suitable areas, essential for planning conservation and management strategies. Unfortunately, often the only available information in such studies is the true presence of the species at few locations of the study area and the associated environmental covariates over the entire area, referred as presence-only data. We propose a Bayesian approach to estimate logistic linear regressions adapted to presence-only data through the introduction of a random approximation of the correction factor in the adjusted logistic model that allows us to overcome the need to know a priori the prevalence of the species.
Descriptive Statistics
2009
A set of medical data is based on a collection of the data of individual cases or objects, also called observation units or statistical units. Every case, for example every study participant, patient, every experimental animal, every tooth or every cell shows comparable parameters (such as body weight, gender, erosion, pH). Each of these parameters, also called variables, has a specific parameter value (gender = male, age = 30 years, weight = 70 kg) for each observation unit (for example the patient). The aim of descriptive statistics is to summarize the data, so that they can be clearly illustrated (1–3). The property of a parameter is specified by its so-called scale of measure. Generally…
Parameter Rating by Diffusion Gradient
2014
Anomaly detection is a central task in high-dimensional data analysis. It can be performed by using dimensionality reduction methods to obtain a low-dimensional representation of the data, which reveals the geometry and the patterns that exist and govern it. Usually, anomaly detection methods classify high-dimensional vectors that represent data points as either normal or abnormal. Revealing the parameters (i.e., features) that cause detected abnormal behaviors is critical in many applications. However, this problem is not addressed by recent anomaly-detection methods and, specifically, by nonparametric methods, which are based on feature-free analysis of the data. In this chapter, we provi…
MDA: a MATLAB-based program for morphospace-disparity analysis
2003
A MATLAB® program that examines patterns of state-space occupation is described. Four subroutines are available with which to visualize morphospace patterns: (i) in terms of their features such as dispersion, aggregation and location, thereby allowing users to extract complementary quantitative information about how the state-space is structured, and (ii) in terms of changes in those patterns that can be compared with other biotic (e.g., extinction, origination rates) or abiotic (e.g., environmental proxy) information. The program incorporates many of the latest and most widely used statistical parameters for describing multivariate spaces. The parameters are estimated on the basis of boots…
Hierarchically nested factor model from multivariate data
2005
We show how to achieve a statistical description of the hierarchical structure of a multivariate data set. Specifically we show that the similarity matrix resulting from a hierarchical clustering procedure is the correlation matrix of a factor model, the hierarchically nested factor model. In this model, factors are mutually independent and hierarchically organized. Finally, we use a bootstrap based procedure to reduce the number of factors in the model with the aim of retaining only those factors significantly robust with respect to the statistical uncertainty due to the finite length of data records.
Integration of high and low resolution NDVI data for monitoring vegetation in Mediterranean environments
1998
Abstract The integration of the useful features of high and low spatial and temporal resolution satellite data is a major issue in remote sensing studies. The current work presents the development and testing of a procedure based on classification and regression analysis techniques for generating an NDVI data set with the spatial resolution of Landsat TM images and the temporal resolution of NOAA AVHRR maximum-value composites. The procedure begins with a classification of the high resolution TM data which yields land use references. These are degraded to low spatial resolution in order to produce abundance images comparable with the AVHRR data. Linear regressions are then applied between t…
The Analysis of Auxological Data by Means of Nonlinear Multivariate Growth Curves
1999
In this paper we treat the problem to analyse a data set constituted by multivariate growth curves for different subjects; thus in this context we deal with 3-way data tables. Nevertheless, it is not possible using factorial techniques proposed to deal with 3-way data matrices, because the observations are generally not equally spaced; moreover a multilevel approach founded on polynomial models is not suitable to deal with intrinsic nonlinear models. We propose a non-factorial technique to analyse auxological data sets using an intrinsic nonlinear multivariate growth model with autocorrelated errors. The application to a real data set of growing children gave easily interpretable results.
Differences in Life Expectancy Between Self-Employed Workers and Paid Employees when Retirement Pensioners: Evidence from Spanish Social Security Rec…
2021
The aim of this paper is to examine differences in life expectancy (LE) between self-employed (SE) and paid employee (PE) workers when they become retirement pensioners, looking at levels of pension income using administrative data from Spanish social security records. We draw on the Continuous Sample of Working Lives (CSWL) to quantify changes in total life expectancy at age 65 (LE(65)) among retired men over the longest possible period covered by this data source: 2005–2018. These changes are broken down by pension regime and initial pension income level for three periods. The literature presents mixed evidence, even for the same country–for Japan and Italy, for example–with some studies …