Sub-sample analysis and removing outliers…
Removing Outliers in Illumination Estimation
... by outliers. Outliers can be due to simple noise or to the presence of unexpected secondary ...and removing these outliers based on the RANSAC algorithm was presented and shown to lead to ...
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Effect of Removing Outliers on Statistical Inference: Implications to Interpretation of Experimental Data in Medical Research
... The open source program R was used for all simulations in this study. 14 To model the effect of outlier exclusion on computed p-values of experiments for which the null hypothesis held, we first drew two data sets from ...
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Topological Analysis of Scalar Fields with Outliers
... each sample back to the closest point on the underlying manifold M, the result is a new set of samples where all points are on the manifold and thus can be seen as having no geometric noise; however, this point ...
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Detection of Upper Outliers in an Exponential Sample using Multiple Outlier Tests
... irregularity analysis, data cleansing, network intrusion, severe weather prediction, geographic information systems, athlete performance analysis, and other data-mining ...
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New models for describing outliers in meta analysis
... Research Synthesis Methods published by John Wiley & Sons, Ltd. Keywords: meta-analysis; outlier; skew distribution; lagged-normal distribution; mixed distribution 1. Introduction In many meta-analyses, the ...
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New models for describing outliers in meta-analysis
... Research Synthesis Methods published by John Wiley & Sons, Ltd. Keywords: meta-analysis; outlier; skew distribution; lagged-normal distribution; mixed distribution 1. Introduction In many meta-analyses, the ...
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ANALYSIS OF HIGH COST OUTLIERS IN A POLISH REFERENCE HOSPITAL
... detecting outliers accounting for an important share of hospital ...cost outliers in one of the Polish reference hospitals in northeast ...Cost analysis was done retrospectively using accountancy and ...
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1. An experimental analysis of outliers detection on static exaustive datasets.
... of outliers may greatly improve the performance of statistical data mining ...and removing outliers as a preprocessing step using clustering ...
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Large Dimensional Analysis of Robust M-Estimators of Covariance With Outliers
... and sample sizes grow together to infinity. The introduction of outliers leads the robust estimator to behave asymptotically as the weighted sum of the sample outer products, with a constant weight ...
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CHAPTER 13 SUB-ANALYSIS CHAPTER 14 SUB-ANALYSIS
... SEC. 13.07. DEAD OR DISEASED TREE REMOVAL ON PRIVATE PROPERTY The City shall have the right to cause the removal of any dead or diseased trees on public or private property within the City in accordance with this ...
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Abundant topological outliers in social media data and their effect on spatial analysis
... Then, starting from that point, 500 points were successively placed by choosing a random angle and distance at each step, both of which are following a uniform distribution constrained by the abovementioned distance ...
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Bayesian Analysis to the Detection of Outliers in an Autoregressive Model with Exponential White Noise
... The parameters , δ and α are unknown. We also define y T =(y 1, y 2 ..... y n ) as a vector of r unities and (n-r) zero where r and hence x are unknown. Assuming x to be known, Fox 5 considered a likelihood ratio ...
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The Outliers and Prediction Analysis of University Talents Introduced Based on Data Mining
... of outliers, their prediction accuracy of the model of talent introduction is relatively ...the outliers successfully. We set up some models to predict after removing those ...
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Estimating population treatment effects from a survey sub-sample
... a sub-sample of 2,490 participants because of budget ...participants. Analysis of the relationship between neighbor- hood disadvantage and cortisol slope among the sub-sample of ...
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On the conditional behavior of stock market volatility: a sub-sample analysis using the FIGARCH approach for developed and emerging markets
... S.R. Bentes ∗ Instituto Superior de Contabilidade e Administração de Lisboa (ISCAL), Lisboa, Portugal and Instituto Universitário de Lisboa (ISCTE-IUL), Business Research Unit (BRU-IUL), Lisboa, Portugal Long memory has ...
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Multiple Imputation in the Presence of Outliers
... of Outliers Michael ...and outliers in the context of estimating obesity prevalence and body-mass index (BMI) measures from the Healthy For Life ...multiple outliers in a multivariate setting is ...
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Detecting Outliers and Influential Data Points in Receiver Operating Characteristic (ROC) Analysis
... The parametric test statistic provided reasonable type I error for both small and large sample sizes and for all considered AUCs. In addition, in our limited simulation study reasonable power was achieved for the ...
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Robust Decision Trees: Removing Outliers from Databases. George H. John
... Pruning is a method of local data selection, since records are effectively removed from nodes deep in the tree - pruning a node to a leaf has the same effect as remov[r] ...
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Cointegration Analysis in the Presence of Outliers
... As an alternative to the original model we apply the automatic outlier detection procedure, and Table 2 reports the outliers detected in each iteration. In first iteration the observation 1973 : 2 is chosen to be ...
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Analysis of lightning outliers in the EUCLID network
... Figure 6 illustrates the monthly variation of the percentage of outliers. An obvious decrease is observed in the percent- age of outliers during May–September, compared to the other months of the year. This ...
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