Sentence examples for classical statistical methods from inspiring English sources
Classical statistics grew out of a frequentist interpretation of probability, and accordingly the probabilities appearing in the classical statistical methods are all interpreted as frequencies of events.
A detailed analysis of correlation between wind and building pressure is difficult using classical statistical methods.
Classical statistical methods rely on the analytical power of mathematics and some assumptions rather than on computer power.
This introductory course is a practicum in which students will learn the basics of R and use the programming language to analyze health datasets by application of classical statistical methods.
Naturally, the data set from the supposed hiatus period is much smaller — so small, in fact, that it would be hard to get accurate results using most classical statistical methods, says Bala Rajaratnam, the study's lead author and an assistant professor of statistics and Earth system science at Stanford University.
The underlying formulation of support vector machines embodies the structural risk minimization (SRM) principle which has been shown to be superior to the traditional empirical risk minimization (ERM) principle employed by conventional neural networks and classical statistical methods.
The most classical statistical method is to exploit classifiers or regression methods to recognize specific discrete head poses.
Principal component analysis (PCA) is a classical statistical method known as a linear transform that has been widely used in data analysis and compression.
Discriminant analysis is a classical statistical method to separate two or more classes of objects based on the distance between them.
We estimated the risk of breast cancer for individuals with the T1a1 haplogroup compared with individuals with another T subclade haplogroup in the population of BRCA2 mutation carriers using a more classical statistical method, a weighted Cox regression.
A widely known classical statistical method for finding dependencies between datasets is canonical correlation analysis [CCA; Hotelling, 1936], for which there exist recent sparse variants (Archambeau and Bach, 2009; Parkhomenko et al., 2007; Waaijenborg and Zwinderman, 2007; Witten and Tibshirani, 2009).
