نتایج جستجو برای: gradual omission of outliers
تعداد نتایج: 21165464 فیلتر نتایج به سال:
One of the crime that to be discus in special criminal law as crime against persons is abstain of help to dangered persons. Despite this crime is old in criminal statute of Iran but has not enough research. Essens for criminality in this omission is ethical principles and social co-operative . This article will research elements of this crime after analyze origin of its criminality. In first se...
Parameter estimation is the first step in constructing any control chart. Most estimators of mean and dispersion are sensitive to the presence of outliers. The data may be contaminated by outliers either locally or globally. The exciting robust estimators deal only with global contamination. In this paper a robust estimator for dispersion is proposed to reduce the effect of local contamination ...
The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection an...
We read with great interest a recent article entitled “Posterior Mediastinal Sarcoidosis” by Rosseel et al (Chest 1986; 90:462-64). As the authors indicate, posterior mediastmnal lymphadenopathy in sarcoidosis has rarely been recorded. It may be expected that frequent use of CT in these cases may change our current concept about the incidence of such involvement in the disease, and additional w...
Background and purpose: By evolving science, knowledge, and technology, we deal with high-dimensional data in which the number of predictors may considerably exceed the sample size. The main problems with high-dimensional data are the estimation of the coefficients and interpretation. For high-dimension problems, classical methods are not reliable because of a large number of predictor variable...
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