Non-parametric statistic method based on Kolmogorov-
Comparison of reliability techniques of parametric and non-parametric method
... was based on measuring the current leakages in the electrical device, which consist of a ripple of source and the measuring ...obtained based on the failure mode observed in the ...
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An Adaptive Non-parametric Kernel Method for Classification
... Adaptive Non–Parametric Kernel Method for Classi- fication (Under the direction of ...statistical method of estimating an underlying distribution from a set of samples is the ...
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Bayesian non parametric inference for Λ coalescents : posterior consistency and a parametric method
... The rest of the paper is laid out as follows. Section 2 provides an introduction to Λ- coalescents, Λ-Fleming-Viot jump-diffusions and a duality relation connecting the two. In Section 3 we state and prove our ...
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A non-parametric method to nowcast the Euro Area IPI
... whether non-parametric statistical procedures based on a Kernel method can improve classical linear models in order to nowcast the Euro area manufacturing industrial production index (IPI) by ...
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Non parametric wavelet based texture synthesis
... 4. EXPERIMENTAL VALIDATION An experiment has been conducted to compare the learning capability of the method when applied with the three pro- posed criteria. We focussed on Gaussian data of constant mean ...
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A Survey Report on Non-Parametric Hypothesis Testing Including Kruskal-Wallis ANOVA and Kolmogorov Smirnov Goodness-Fit-Test
... mean based on the assumption about symmetric ...effective method among ranking test ...time. Kolmogorov–Smirnov goodness-fit-test section focuses on different hypothesis, which measure the ...
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Cash and profit efficient in Malaysia and South Korea listed company using non-parametric DEA method and parametric regression method
... generated based on a frontier, by developing all the observed input-output ...This method presumes that if a firm can generate a certain level of output using particular input levels, another firm of equal ...
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Developing Non-Parametric Density Estimation on Genetic Evolution Computing as a Cloud Based Sensor Fusion Method
... proposed method which keeps the same performance of the accuracy to compare with the pure PWD method, even values of features shift caused from mental stage ...
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A Non parametric RDP Algorithm Based on Leap Motion
... algorithm based on the fixed parameter. Through this method, we can detect the points which are insensitive to the digitization noise of the digital ...point based detection algorithm can ...
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Propensity score method: a non parametric technique to reduce model dependence
... balance statistic, the subscript α is to denote a particular subclassification scheme, K is the total number of stratum, and µ ˆ 0 k and µ ˆ 1 k are mean values of the control and treated group within stratum ...
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Application of a non-parametric method to analyze energy consumption for orange production
... holdings in the target population; S is the standard deviation; T is the t-value at a 95% confidence limit (1.96); and d is the acceptable error (permissible error 5%). The calculated sample size in this study was ...
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Bootstrapping the economy a non parametric method of generating consistent future scenarios
... A way to disentangle the complex dynamics and dependencies of interest rates – both in market practice and in modeling – is using forward interest rate or IR futures. Using IR futures is the most consequent solution, as ...
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A New Stylometry Method Basing on the Numerals Statistic
... new method of statistical analysis of texts is ...of non- parametric range Mann-Whitney and Kruskal-Wallis tests as well as the parametric Pearson's chi-squared ...
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Parametric and Bayesian non-parametric estimation of copulas.
... the parametric family of the Archimedean ...a method for the estimation of a vector-parameter family where the approach introduced by Genest and Rivest (1993) appears to be ...our method can be ...
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Parametric Method Based PSD Estimation using Gaussian Window
... Abstract- Non-parametric methods of Spectrum Estimation Such as Periodogram, Modified Periodogram, Welch, Bartlett and Blackman-Tukey are generally used but are not always efficient in finding out the power ...
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Unsupervised Color Image Segmentation Based on Non Parametric Clustering
... Department of Computer Science, Univesity of Badji Mokhtar, Annaba, Algeria Many segmentation problems have been addressed using probabilistic modeling. These methods tend to estimate the region membership probabilities ...
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A Nonlinear Causality Estimator Based on Non-Parametric Multiplicative Regression
... be non-stationary and it may be more difficult to isolate task-related connectivity; particularly, when connectivity occurs at a time frame that is much shorter than the window length it is possible that this is ...
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Optimization-based approaches to non-parametric extreme event estimation
... tractable method- ology to compute confidence bounds for extremal quantities by solving ...derivative- based constraints, the latter being a way to capture belief on the tail distributional ...conventional ...
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Example-based Facial Sketch Generation with Non-parametric Sampling
... ¿ Xi’an Jiaotong University, China Abstract In this paper, we present an example-based facial sketch system. Our system automatically generates a sketch from an input image, by learning from example sketches drawn ...
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Modelling health state preference data using a non-parametric Bayesian method
... 1. Introduction There has been an increasing use of preference-based measures of health related quality of life in order to calculate quality adjusted life years for use in cost effectiveness analyses. These ...
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