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1. Manifold based on neighbour mapping and its projection for remote sensing image segmentation

Author:
Zhao, Xuemei; Li, Yu; Wang, Haijian
Source:
International journal of remote sensing 2019 v.40 no.24 pp. 9304-9320
ISSN:
1366-5901
Subject:
normal distribution,   etc   ; algorithms; remote sensing;     Show all 3 Subjects
Abstract:
... To accurately describe the features of a remote sensing image by considering the relationship in the neighbourhood system, this paper presents a neighbour mapping and manifold projection-based image segmentation algorithm called NM_MP (Neighbour Mapping and Manifold Projection, NM_MP). First, the features of the image are described by Gaussian distributions. Then, the image described by the Gaussi ...
DOI:
10.1080/01431161.2019.1629718

2. Flexible parametric approach to classical measurement error variance estimation without auxiliary data

Author:
Bertrand, Aurélie; Van Keilegom, Ingrid; Legrand, Catherine
Source:
Biometrics 2019 v.75 no.1 pp. 297-307
ISSN:
0006-341X
Subject:
normal distribution,   etc   ; algorithms; biometry; models; variance;     Show all 5 Subjects
Abstract:
... Measurement error in the continuous covariates of a model generally yields bias in the estimators. It is a frequent problem in practice, and many correction procedures have been developed for different classes of models. However, in most cases, some information about the measurement error distribution is required. When neither validation nor auxiliary data (e.g., replicated measurements) are avail ...
DOI:
10.1111/biom.12960

3. Introducing an integral optimised warping (IOW) approach for achieving swift alignment of drifted chromatographic peaks: an optimisation of the correlation optimised warping (COW) technique

Author:
Kumar, Keshav
Source:
Analytical methods 2018 v.10 no.23 pp. 2764-2774
ISSN:
1759-9679
Subject:
normal distribution,   etc   ; algorithms; chromatography;     Show all 3 Subjects
Abstract:
... The drift in the position of chromatographic peaks is an unavoidable problem that needs to be taken care of before subjecting them to any data analysis work packages. The correction is essential because each of these data analysis work packages compares the chromatograms at each retention time point. Thus, it is important that a peak if present in all chromatograms must appear at the same retentio ...
DOI:
10.1039/c8ay00963e

4. Estimating the mean and variance of a high-dimensional normal distribution using a mixture prior

Author:
Sinha, Shyamalendu; Hart, Jeffrey D.
Source:
Computational statistics & data analysis 2019 v.138 pp. 201-221
ISSN:
0167-9473
Subject:
normal distribution,   etc   ; algorithms; models; shrinkage; variance; variance covariance matrix;     Show all 6 Subjects
Abstract:
... A framework is provided for estimating the mean and variance of a high-dimensional normal density. The main setting considered is a fixed number of vectors following a high-dimensional normal distribution with unknown mean and diagonal covariance matrix. The diagonal covariance matrix can be known or unknown. If the covariance matrix is unknown, the sample size can be as small as 2. The proposed e ...
DOI:
10.1016/j.csda.2019.04.006

5. Lameness detection of dairy cows based on a double normal background statistical model

Author:
Jiang, Bo; Song, Huaibo; He, Dongjian
Source:
Computers and electronics in agriculture 2019 v.158 pp. 140-149
ISSN:
0168-1699
Subject:
normal distribution,   etc   ; algorithms; animal welfare; dairy cows; lameness; statistical models;     Show all 6 Subjects
Abstract:
... Dairy cow lameness is one of the diseases that affect the health of dairy cows, and the rapid and accurate detection of dairy cow lameness is an important research field for modern dairy cow farming. In this study, a lameness detection method based on a double normal distribution statistical model was proposed. The combination of these features could be used to determine the lameness of dairy cows ...
DOI:
10.1016/j.compag.2019.01.025

6. Estimation of the minimum spouting velocity in shallow spouted beds by intelligent approaches: Study of fine and coarse particles

Author:
Hosseini, S.H.; Rezaei, M.J.; Bag-Mohammadi, M.; Karami, M.; Moradkhani, M.A.; Panahi, M.; Olazar, M.
Source:
Powder technology 2019 v.354 pp. 456-465
ISSN:
0032-5910
Subject:
normal distribution,   etc   ; algorithms; data collection; hydrodynamics; models; particle size; powders; system optimization;     Show all 8 Subjects
Abstract:
... The minimum spouting velocity, which is an essential parameter in the design and scale-up spouted beds, has been predicted by different intelligent methods for shallow spouted beds of fine and coarse dense-particles. Four important dimensionless moduli, namely, Ar, Hb/Do, Do/Dc, and tan(γ/2) have been taken as model inputs. A single correlation for the minimum spouting velocity in the whole range ...
DOI:
10.1016/j.powtec.2019.06.025

7. Efficient variography with partition variograms

Author:
Hoffimann, Júlio; Zadrozny, Bianca
Source:
Computers & geosciences 2019
ISSN:
0098-3004
Subject:
normal distribution,   etc   ; algorithms; computers; data collection; geostatistics; industry; petroleum; spatial data; wells;     Show all 9 Subjects
Abstract:
... Directional variograms were introduced in geostatistics as a tool for revealing major directions of correlation in spatial data. However, their estimation presents some practical challenges, particularly in the case of large irregularly-sampled data sets where efficient spectral-based estimation methods are not applicable. In this work, we propose a generalization of directional variograms to gene ...
DOI:
10.1016/j.cageo.2019.06.013

8. Multi‐scale Gaussian/Haar wavelet strategies coupled with sub‐window factor analysis for an accurate alignment in nontargeted metabolic profiling to enhance herbal origin discrimination capability

Author:
He, Min; Hong, Liang; Zhou, Yu
Source:
Journal of separation science 2019 v.42 no.11 pp. 2003-2012
ISSN:
1615-9306
Subject:
normal distribution,   etc   ; Bupleurum; algorithms; chromatography; data collection; factor analysis; metabolomics; wavelet;     Show all 8 Subjects
Abstract:
... Metabolic dataset can provide an overview of different herbal origin, which is conducted by some statistical procedures. Such results often deviate to a certain degree, due to peaks shifts in chromatographic signals. In order to solve this problem, an improved algorithm of combining sub‐window factor analysis with the mass spectrum information is proposed. The algorithm uses a peak detection appro ...
DOI:
10.1002/jssc.201801077

9. Operational Flood Detection Using Sentinel-1 SAR Data over Large Areas

Author:
Cao, Han; Zhang, Hong; Wang, Chao; Zhang, Bo
Source:
Water 2019 v.11 no.4
ISSN:
2073-4441
Subject:
normal distribution,   etc   ; Landsat; algorithms; floodplains; rain; rivers; synthetic aperture radar; tiles; wind;     Show all 9 Subjects
Abstract:
... Unsupervised flood detection in large areas using Synthetic Aperture Radar (SAR) data always faces the challenge of automatic thresholding, because the histograms of large-scale images are unimodal, which thus makes it difficult to determine the threshold. In this paper, an iteratively multi-scale chessboard segmentation-based tiles selection method is introduced. This method includes a robust sea ...
DOI:
10.3390/w11040786

10. On the Application of Statistical Analysis for Interpretation of Experimental Results in Environmental Microbiology

Author:
Kallistova, A. Yu.; Sabrekov, A. F.; Goncharov, V. M.; Pimenov, N. V.; Glagolev, M. V.
Source:
Microbiology 2019 v.88 no.2 pp. 232-239
ISSN:
0026-2617
Subject:
normal distribution,   etc   ; algorithms; analysis of variance; computer software; data collection; isotopes; microbiology; t-test;     Show all 8 Subjects
Abstract:
... Statistical analysis is an integral part of every experiment, since it helps researchers to make conclusions out of the work done. Textbooks with detailed description of the algorithms for statistical analysis exist, as well as diverse software packages. Statistical methods are, however, often applied incorrectly, which leads to erroneous and inadequate conclusions. The present article is an attem ...
DOI:
10.1134/S002626171902005X

11. Modelling the variability of hillslope drainage using grid-based hillslope width function estimation algorithm

Author:
Sahoo, Soumyaranjan; Sahoo, Bhabagrahi
Source:
ISH journal of hydraulic engineering 2019 v.25 no.1 pp. 71-78
ISSN:
2164-3040
Subject:
normal distribution,   etc   ; algorithms; dynamic models; streams; subsurface drainage; subsurface flow; topographic slope; water table; watersheds;     Show all 9 Subjects
Abstract:
... Due to the lack of observed groundwater table data and micro-scale topography of the hillslopes constituting a watershed, quantification of subsurface flow using the existing models becomes very difficult. In this context, a low dimensional hillslope storage dynamic model has been developed in this study to represent the physical behaviour of the watershed at the hillslope-scale. The topographic c ...
DOI:
10.1080/09715010.2018.1441750

12. Multispectral change detection using multivariate Kullback-Leibler distance

Author:
Jabari, Shabnam; Rezaee, Mohammad; Fathollahi, Fatemeh; Zhang, Yun
Source:
ISPRS journal of photogrammetry and remote sensing 2019 v.147 pp. 163-177
ISSN:
0924-2716
Subject:
normal distribution,   etc   ; algorithms; data collection; image analysis; probability; remote sensing; urban areas;     Show all 7 Subjects
Abstract:
... Change detection is one of the most critical applications in remote sensing. However, distinguishing between changes and non-changes in images collected at different dates and different imaging platforms is challenging. This is because the image dissimilarities caused by the difference in imaging conditions can mislead the change detection algorithms and result in false alarms. This problem is eve ...
DOI:
10.1016/j.isprsjprs.2018.11.014

13. Calculation of the Infrared Intensity of Crystalline Systems. A Comparison of Three Strategies Based on Berry Phase, Wannier Function, and Coupled-Perturbed Kohn–Sham Methods

Author:
Dovesi, R.; Kirtman, B.; Maschio, L.; Maul, J.; Pascale, F.; Rérat, M.
Source:
Journal of physical chemistry 2018 v.123 no.13 pp. 8336-8346
ISSN:
1932-7455
Subject:
normal distribution,   etc   ; algorithms; crystals; physical chemistry;     Show all 4 Subjects
Abstract:
... Three alternative strategies for the calculation of the IR intensity of crystalline systems, as determined by Born charges, have been implemented in the Crystal code, using a Gaussian type basis set. One uses the Berry phase (BP) algorithm to compute the dipole moment; another does so, instead, through well localized crystalline orbitals (Wannier functions, WF); and the third is based on a coupled ...
DOI:
10.1021/acs.jpcc.8b08902

14. The Emergency Vehicle Routing Problem with Uncertain Demand under Sustainability Environments

Author:
Qin, Jin; Ye, Yong; Cheng, Bi-rong; Zhao, Xiaobo; Ni, Linling
Source:
Sustainability 2017 v.9 no.2
ISSN:
2071-1050
Subject:
normal distribution,   etc   ; algorithms; models;     Show all 3 Subjects
Abstract:
... The reasonable utilization of limited resources is critical to realize the sustainable developments. In the initial 72-h crucial rescue period after the disaster, emergency supplies have always been insufficient and the demands in the affected area have always been uncertain. In order to improve timeliness, utilization and sustainability of emergency service, the allocation of the emergency suppli ...
DOI:
10.3390/su9020288

15. Bayesian additive adaptive basis tensor product models for modeling high dimensional surfaces: an application to high‐throughput toxicity testing

Author:
Wheeler, Matthew W.
Source:
Biometrics 2019 v.75 no.1 pp. 193-201
ISSN:
0006-341X
Subject:
normal distribution,   etc   ; Bayesian theory; United States Environmental Protection Agency; algorithms; biometry; data collection; dose response; models; toxicity testing;     Show all 9 Subjects
Abstract:
... Many modern datasets are sampled with error from complex high‐dimensional surfaces. Methods such as tensor product splines or Gaussian processes are effective and well suited for characterizing a surface in two or three dimensions, but they may suffer from difficulties when representing higher dimensional surfaces. Motivated by high throughput toxicity testing where observed dose‐response curves a ...
DOI:
10.1111/biom.12942

16. Diagnosing misspecification of the random‐effects distribution in mixed models

Author:
Drikvandi, Reza; Verbeke, Geert; Molenberghs, Geert
Source:
Biometrics 2017 v.73 no.1 pp. 63-71
ISSN:
0006-341X
Subject:
normal distribution,   etc   ; algorithms; biometry; models;     Show all 4 Subjects
Abstract:
... It is traditionally assumed that the random effects in mixed models follow a multivariate normal distribution, making likelihood‐based inferences more feasible theoretically and computationally. However, this assumption does not necessarily hold in practice which may lead to biased and unreliable results. We introduce a novel diagnostic test based on the so‐called gradient function proposed by Ver ...
DOI:
10.1111/biom.12551

17. Accelerating pseudo-marginal MCMC using Gaussian processes

Author:
Drovandi, Christopher C.; Moores, Matthew T.; Boys, Richard J.
Source:
Computational statistics & data analysis 2018 v.118 pp. 1-17
ISSN:
0167-9473
Subject:
normal distribution,   etc   ; Bayesian theory; Markov chain; algorithms; models;     Show all 5 Subjects
Abstract:
... The grouped independence Metropolis–Hastings (GIMH) and Markov chain within Metropolis (MCWM) algorithms are pseudo-marginal methods used to perform Bayesian inference in latent variable models. These methods replace intractable likelihood calculations with unbiased estimates within Markov chain Monte Carlo algorithms. The GIMH method has the posterior of interest as its limiting distribution, but ...
DOI:
10.1016/j.csda.2017.09.002

18. Gibbs sampling on large lattice with GMRF

Author:
Marcotte, Denis; Allard, Denis
Source:
Computers & geosciences 2018 v.111 pp. 190-199
ISSN:
0098-3004
Subject:
normal distribution,   etc   ; algorithms; computers; probabilistic models; variance covariance matrix;     Show all 5 Subjects
Abstract:
... Gibbs sampling is routinely used to sample truncated Gaussian distributions. These distributions naturally occur when associating latent Gaussian fields to category fields obtained by discrete simulation methods like multipoint, sequential indicator simulation and object-based simulation. The latent Gaussians are often used in data assimilation and history matching algorithms. When the Gibbs sampl ...
DOI:
10.1016/j.cageo.2017.11.012

19. Optimizing the process of reference selection for correlation optimised warping (COW) and interval correlation shifting (icoshift) analysis: automating the chromatographic alignment procedure

Author:
Kumar, Keshav
Source:
Analytical methods 2018 v.10 no.2 pp. 190-203
ISSN:
1759-9679
Subject:
normal distribution,   etc   ; algorithms; chromatography; food industry; metabolomics; proteomics;     Show all 6 Subjects
Abstract:
... In order to ensure that the results of chromatographic data analysis workflow are well within the chemical and biological premise, the same chromatographic peak must be present at the same position for all the analysed samples. The correlation optimised warping (COW) and interval correlation shifting (icoshift) algorithm are the two most commonly used approaches that are used to correct the drifts ...
DOI:
10.1039/c7ay02340e

20. Exact Bayesian inference in spatiotemporal Cox processes driven by multivariate Gaussian processes Series B Statistical methodology

Author:
Gonçalves, Flávio B.; Gamerman, Dani
Source:
Journal of the Royal Statistical Society 2018 v.80 no.1 pp. 157-175
ISSN:
1369-7412
Subject:
normal distribution,   etc   ; Bayesian theory; Markov chain; algorithms; equations; models;     Show all 6 Subjects
Abstract:
... We present a novel inference methodology to perform Bayesian inference for spatiotemporal Cox processes where the intensity function depends on a multivariate Gaussian process. Dynamic Gaussian processes are introduced to enable evolution of the intensity function over discrete time. The novelty of the method lies on the fact that no discretization error is involved despite the non‐tractability of ...
DOI:
10.1111/rssb.12237