Results 21 to 30 of about 263,405 (267)
Journal of Statistical Software, 2020 We introduce Sim.DiffProc, an R package for symbolic and numerical computations on scalar and multivariate systems of stochastic differential equations (SDEs). It provides users with a wide range of tools to simulate, estimate, analyze, and visualize the
Arsalane Chouaib Guidoum +1 more
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kdecopula: An R Package for the Kernel Estimation of Bivariate Copula Densities
Journal of Statistical Software, 2018 We describe the R package kdecopula (current version 0.9.2), which provides fast implementations of various kernel estimators for the copula density. Due to a variety of available plotting options it is particularly useful for the exploratory analysis of
Thomas Nagler
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Online nonparametric Bayesian analysis of parsimonious Gaussian mixture models and scenes clustering
ETRI Journal, 2020 The mixture model is a very powerful and flexible tool in clustering analysis. Based on the Dirichlet process and parsimonious Gaussian distribution, we propose a new nonparametric mixture framework for solving challenging clustering problems. Meanwhile,
Ri‐Gui Zhou, Wei Wang
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Nonparametric and Semi‐Nonparametric Recreational Demand Analysis [PDF]
American Journal of Agricultural Economics, 2000 AbstractThis paper addresses issues of specification testing for the travel cost method (TCM). Two nonparametric approaches to TCM analysis are presented. In addition, semi‐nonparametric count models for TCM are developed. A numerical illustration is provided in which the three methods are applied to an actual TCM data set on waterfowl hunting and the ...
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NONPARAMETRIC SIGNIFICANCE TESTING [PDF]
Econometric Theory, 2000 A procedure for testing the significance of a subset of explanatory variables in a nonparametric regression is proposed. Our test statistic uses the kernel method. Under the null hypothesis of no effect of the variables under test, we show that our test statistic has an nhp2/2 standard normal limiting distribution, where p2 is the dimension of ...
Lavergne, Pascal, Vuong, Quang H.
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Integrated model for genomic prediction under additive and non-additive genetic architecture
Frontiers in Plant Science, 2022 Using data from genome-wide molecular markers, genomic selection procedures have proved useful for estimating breeding values and phenotypic prediction. The link between an individual genotype and phenotype has been modelled using a number of parametric ...
Neeraj Budhlakoti +6 more
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Ecology and Evolution, 2022 By measuring the temporal consistency, or repeatability, in the diets of predators, we can gain a better understanding of the degree of individual specialization in resource utilization and implications for predator–prey interactions, population dynamics,
Connie Stewart +3 more
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Comparison of Parametric and Nonparametric Forecasting Methods for Daily COVID-19 Cases in Malaysia
JOIV: International Journal on Informatics Visualization, 2023 Numerous research studies are currently examining various measures to control the transmission of COVID-19. One essential task in this regard is predicting or forecasting the number of infected individuals.
I Made Artha Agastya, Afrig Aminuddin
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Molecular Oncology, EarlyView.Tumors contain diverse cellular states whose behavior is shaped by context‐dependent gene coordination. By comparing gene–gene relationships across biological contexts, we identify adaptive transcriptional modules that reorganize into distinct vulnerability axes.
Brian Nelson +9 more
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Detect and exploit hidden structure in fatty acid signature data
Ecosphere, 2017 Estimates of predator diet composition are essential to our understanding of their ecology. Although several methods of estimating diet are practiced, methods based on biomarkers have become increasingly common. Quantitative fatty acid signature analysis
Jeffrey F. Bromaghin +2 more
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