Non-parametric statistical test
University website quality comparison by using non-parametric statistical test: a case study from Malaysia. P.D.D. Dominic* and Handaru Jati
... 3 to determine the best ranking method used to evaluate website quality. This research examined the selected Malaysian University websites: USM, UKM, UPM, UUM and UTP. The data of quality website from Malaysian ...
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A non-parametric test for self-similarity and stationarity in network traffic
... 2 Department of Statistics, University of Warwick [email protected] Summary. We develop a non-parametric statistical test for self-similarity based on the crossing tree and use ...
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A non-parametric test for self-similarity and stationarity in network traffic; Preprint version
... a non-parametric statistical test for self-similarity based on the crossing tree and use simulation experiments to test its perfor- ...
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Parametric and non-parametric statistical methods for the life sciences - Session I
... What test to use ? Rank Tests Two independent samples More then two independent samples Two dependent samples More then two dependent samples Ordered hypotheses More Than Two Independent Samples Protoporphyrin ...
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Training Non Parametric Features for Statistical Machine Translation
... Table 1: BLEU scores for GMM features vs the lin- ear baseline, using different selection methods and number of kernels. Perceptron kernels based on the training set im- proved the baseline by 0.5 BLEU points. We mea- ...
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A Two-Sample Non-Parametric Likelihood Ratio Test
... statistics. Statistical tests for the two-sample hy- pothesis are commonly adaptations of tests that an identically and independently dis- tributed sample has a particular, known, ...
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CLOUD: a non-parametric detection test for microbiome outliers
... After fecal DNA isolation (MoBio, Carlsbad, CA fecal DNA kit), amplicons spanning the V4 region of bac- terial 16S rRNA were generated and sequenced using an Illumina MiSeq platform at the University of Min- nesota ...
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Gradient test under non-parametric random effects models
... gradient test on generalised linear models with random ...gradient test using the methodology developed by Peers (1971) and Hayakawa ...the test with the local power of the tests of the likelihood ...
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Morpho-colorimetric and non-parametric analysis in statistical classification of vascular flora
... Goodness-of-Fit Test 4 we compared, two at a time, the empirical distributions of the three color channels of the 23 classes, so as to find out if they differ each ...
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Color Image Retrieval Based on Non-parametric Statistical Tests of Hypotheses
... both the images are same; otherwise, it is assumed that the images belong to different classes, i.e. both images are different. The obtained test statistic values are indexed in ascending order and the image ...
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Non-parametric statistical evaluation of biodiesel emissions from transit buses
... tail-pipe exhaust at an interval of one second. 4.1 Overview of analysis methodology This section presents a summary of the overall methodology used in data analysis. Detailed results are presented later in the chapter. ...
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Predicting bid prices in construction projects using non-parametric statistical models
... Degree of freedom: The degree of freedom allows the user to impose a penalty to the knot selection process to avoid over fitting the model to the data. Three methods are available to select the degree of freedom they ...
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t-tests, non-parametric tests, and large studies—a paradox of statistical practice?
... the statistical method that gives them the smallest ...WMW test pro- duced smaller p-values that the t-test more than 70% of the times when the number of subjects in each group was ...WMW test ...
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Case-Based Statistical Learning: A Non-Parametric Implementation with a Conditional-Error Rate SVM
... Fig. 7. Pre-selection of 20 BAs in light colors using a t-test based feature rank algorithm. CSL approach on the SPECT dataset are summarized in table III, where a linear SVM classifier in a CV loop is used for ...
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Evaluation of Audio Source Separation Models Using Hypothesis-Driven Non-Parametric Statistical Methods
... number of tests performed before comparing them to the ‘significance’ threshold (P < 0.05, typically). III. R ESULTS Figure 1 plots histograms showing the distributions of SDR across songs for each model. In each case, ...
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Non-Parametric Statistical Techniques for Computational Forensic Engineering
... clauses - and solution property S 1 - non-important variables. The solution property is calibrated using rank-order. A rank of one is given to the algorithm with the highest property value on a given instance, and ...
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Statistical Parametric and Non Parametric Methods of Determining the Reliability of Mechanical Components EUR 4282
... sample data. b) It performs the fitting by the least-squares method (minimizing the deviations of the measured variable) and then determines an estimate of the parameters of each distr[r] ...
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A non parametric maximum test for the Behrens–Fisher problem
... t test can become liberal ...Brunner-Munzel test and the Welch t test based on ranks control the type I error rate for a wide range of ...t test was superior to the Brunner-Munzel test ...
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A Non-Parametric Test of the Conditional CAPM for the Mexican Economy
... the test could produce a rejection and large pricing error estimates because of a poor functional ...a non-parametric discount factor we get a weighted least squares estimator for the re- gression ...
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Image Denoising by Non Parametric Statistical Model of Wavelet Coefficients
... a non-parametric statistical model of wavelet coefficient is ...proposed non- parametric statistical model is more suitable than conventional models to formulate the marginal ...
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