Multivariate analyses such as principal component analysis were among the first statistical methods employed to extract information from genetic markers. From their early applications to current ...

The Annals of Mathematical Statistics, Vol. 24, No. 2 (Jun., 1953), pp. 220-238 (19 pages) In this paper two closely related heuristic principles of test construction (to be explained in Section 3), ...

In semiconductor manufacturing, especially in electrical test data, but also in other parameters, there are often sets of parameters that are very highly correlated. Even a change in the correlation ...

Current interest in multivariate analysis in biometrics and other areas of applied statistics must inevitably lead to a scrutiny of the robustness of the procedure ...

Symmetric wavelet frames represent a powerful class of mathematical tools designed for efficient and robust representation of high-dimensional data. They combine the inherent benefits of wavelet ...

This course is available on the MPhil/PhD in Environmental Economics, MPhil/PhD in International Relations, MPhil/PhD in International Relations, MPhil/PhD in Social Policy, MPhil/PhD in Social ...

Customer perceptions of your company's brand are complex and difficult to predict because of the variety of factors involved. Multivariate analysis uses statistical tools such as multiple regression ...

This multivariate analysis also suggested the presence of previously unrecognized subclusters within the favorable prognosis category, indicating the potential for finer risk stratification.

Late effects in long-term survivors of high-grade non-Hodgkin's lymphomas. A retrospective study of patients 60 years of age or older with intermediate- or high-grade NHL treated with CHOP ...