نتایج جستجو برای: non parametric statistics

تعداد نتایج: 1511597  

2016
Nannan Wu Feng Chen Jianxin Li Baojian Zhou Naren Ramakrishnan

Non-parametric graph scan (NPGS) statistics are used to detect anomalous connected subgraphs on graphs, and have a wide variety of applications, such as disease outbreak detection, road traffic congestion detection, and event detection in social media. In contrast to traditional parametric scan statistics (e.g., the Kulldorff statistic), NPGS statistics are free of distributional assumptions an...

Journal: :BMJ 2009
Douglas G Altman J Martin Bland

Continuous data arise in most areas of medicine. Familiar clinical examples include blood pressure, ejection fraction, forced expiratory volume in 1 second (FEV1), serum cholesterol, and anthropometric measurements. Methods for analysing continuous data fall into two classes, distinguished by whether or not they make assumptions about the distribution of the data. Theoretical distributions are ...

Journal: :Bioinformatics 2014
Jun Hu Jung-Ying Tzeng

MOTIVATION Gene set analysis is a popular method for large-scale genomic studies. Because genes that have common biological features are analyzed jointly, gene set analysis often achieves better power and generates more biologically informative results. With the advancement of technologies, genomic studies with multi-platform data have become increasingly common. Several strategies have been pr...

Journal: :Advances in Mathematics 1977

Journal: :Austrian Journal of Statistics 2016

Journal: :The Economic Journal 2004

2012
Aanchal Jain Alexander Wong

Image processing applications such as image denoising, image segmentation, object detection, object recognition and texture synthesis often require a multi-scale analysis of images. This is useful because different features in the image become prominent at different scales. Traditional imaging models, which have been used for multi-scale analysis of images, have several limitations such as high...

2010
Jae Kwang Kim Cindy Long Yu

Parameter estimation with non-ignorable missing data is a challenging problem in statistics. The fully parametric approach for joint modeling of the response model and the population model can produce results that are quite sensitive to the failure of the assumed model. We propose a more robust modeling approach by considering the model for the nonresponding part as an exponential tilting of th...

Journal: :The Annals of Mathematical Statistics 1948

2013
Deepika Singh

In this paper, we focus on the experimental analysis on the performance in cluster analysis with the use of nonparametric tests on the clustering task. Particularly, we have studied whether the sample of results from multiple trials obtained by conventional clustering algorithms checks the necessary conditions for being analyzed through parametrical tests. The study is conducted by considering ...

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