Search results for "Statistic"

Overland flow generation on hillslopes of complex topography: analytical Solutions

2007

The analytical solution of the overland flow equations developed by Agnese et al. (2001; Hydrological Processes15: 3225–3238) for rectangular straight hillslopes was extended to convergent and divergent surfaces and to concave and convex profiles. Towards this aim, the conical convergent and divergent surfaces are approximated by a trapezoidal shape, and the overland flow is assumed to be always one-dimensional. A simple ‘shape factor’ accounting for both planform geometry and profile shape was introduced: for each planform geometry, a brachistochrone profile was obtained by minimizing a functional containing a slope function of the profile. Minima shape factors are associated with brachist…

Comment on "Estimating average annual per cent change in trend analysis"

2010

We discuss some issues relevant to paper of Clegg and co-authors published in Statistics in Medicine; 28, 3670-3682. Emphasis is on computation of the variance of the sum of products of two estimates, slopes and breakpoints.

The determination of maturity stages in male elasmobranchs (Chondrichthyes) using a segmented regression of clasper length on total length

2013

A novel statistical method for estimating the stages of maturity in male sharks and skates based on a segmented regression (SRM) is proposed. We hypothesize that this method is able to find the transition points in the three-phase relationship between total length (TL) and clasper length (CL). We applied an SRM to TL–CL data of nine species, from large pelagic sharks (e.g., Carcharhinus falciformis) to small coastal skates (e.g., Rioraja agassizi), captured in the southwestern Atlantic and northeastern Pacific. As expected, SRM detected two breakpoints, defining three maturity stages (immature, maturing, and mature), in six out of nine species. For three species, it was not possible to fin…

Learning-based multiresolution transforms with application to image compression

2013

In Harten's framework, multiresolution transforms are defined by predicting finer resolution levels of information from coarser ones using an operator, called prediction operator, and defining details (or wavelet coefficients) that are the difference between the exact and predicted values. In this paper we use tools of statistical learning in order to design a more accurate prediction operator in this framework based on a training sample, resulting in multiresolution decompositions with enhanced sparsity. In the case of images, we incorporate edge detection techniques in the design of the prediction operator in order to avoid Gibbs phenomenon. Numerical tests are presented showing that the …

Assessing the efficiency of Chilean water and sewerage companies accounting for uncertainty

2016

Abstract Efficiency assessment of water and sewerage companies (WaSCs) has attracted considerable attention both for water company managers and water regulators. Within the methodological approaches that can be applied to estimate efficiency scores, data envelopment analysis (DEA) is the most widely applied technique. In spite of the positive features of DEA, it presents a major drawback which is its deterministic nature. In other words, conventional DEA models do not account for uncertainty in the data. To overcome this limitation, we assess, for the first time, the efficiency of a sample of Chilean WaSCs by using a DEA model with statistical tolerance in the data. Hence, 81 efficiency sco…

2020

To successfully learn using open Internet resources, students must be able to critically search, evaluate and select online information, and verify sources. Defined as critical online reasoning (COR), this construct is operationalized on two levels in our study: (1) the student level using the newly developed Critical Online Reasoning Assessment (CORA), and (2) the online information processing level using event log data, including gaze durations and fixations. The written responses of 32 students for one CORA task were scored by three independent raters. The resulting score was operationalized as “task performance,” whereas the gaze fixations and durations were defined as indicators of “pr…

贝叶斯因子及其在JASP中的实现

2018

Statistical inference plays a critical role in modern scientific research, however, the dominant method for statistical inference in science, null hypothesis significance testing (NHST), is often misunderstood and misused, which leads to unreproducible findings. To address this issue, researchers propose to adopt the Bayes factor as an alternative to NHST. The Bayes factor is a principled Bayesian tool for model selection and hypothesis testing, and can be interpreted as the strength for both the null hypothesis H0 and the alternative hypothesis H1 based on the current data. Compared to NHST, the Bayes factor has the following advantages: it quantifies the evidence that the data provide for…

Spectral clustering with the probabilistic cluster kernel

2015

Abstract This letter introduces a probabilistic cluster kernel for data clustering. The proposed kernel is computed with the composition of dot products between the posterior probabilities obtained via GMM clustering. The kernel is directly learned from the data, is parameter-free, and captures the data manifold structure at different scales. The projections in the kernel space induced by this kernel are useful for general feature extraction purposes and are here exploited in spectral clustering with the canonical k-means. The kernel structure, informative content and optimality are studied. Analysis and performance are illustrated in several real datasets.

Automating statistical diagrammatic representations with data characterization

2017

The search for an efficient method to enhance data cognition is especially important when managing data from multidimensional databases. Open data policies have dramatically increased not only the volume of data available to the public, but also the need to automate the translation of data into efficient graphical representations. Graphic automation involves producing an algorithm that necessarily contains inputs derived from the type of data. A set of rules are then applied to combine the input variables and produce a graphical representation. Automated systems, however, fail to provide an efficient graphical representation because they only consider either a one-dimensional characterizat…

Multiple Classifiers and Data Fusion for Robust Diagnosis of Gearbox Mixed Faults

2019

Detection and isolation of single and mixed faults in a gearbox are very important to enhance the system reliability, lifetime, and service availability. This paper proposes a hybrid learning algorithm, consisting of multilayer perceptron (MLP)- and convolutional neural network (CNN)-based classifiers, for diagnosis of gearbox mixed faults. Domain knowledge features are required to train the MLP classifier, while the CNN classifier can learn features itself, allowing to reduce the required knowledge features for the counterpart. Vibration data from an experimental setup with gearbox mixed faults is used to validate the effectiveness of the algorithms and compare them with conventional metho…