Hasil untuk "Analysis"

A. Mitscherlich

A GOOD and clear translation of Freud's short essay on group psychology is given by Mr. Strachey. The work begins by a brief examination of the views of earlier writers, particularly of Le Bon and M'Dougall. Freud's own method of approach to social psychology is naturally by way of an analysis of the motives of individual behaviour. He treats the group as a collection of persons bound together by some form of love relationship, and to the formation of the group ascribes what to many will appear to be an overweighted importance to the leader. His discussions of the phenomena of “identification,” and of the relations of “being in love and hypnosis,” are interesting in themselves; but his application of the results of his discussions to the explanation of social behaviour is not convincing.Group Psychology and the Analysis of the Ego.By Dr. Sigm. Freud. Authorised translation by James Strachey. (The International Psycho-Analytical Library, No. 6.) Pp. v + 134. (London: G.Allen and Unwin, Ltd., 1922.) 7s. 6d. net.

Gennady Korotkevich, V. Sukhov, A. Sergushichev

Preranked gene set enrichment analysis (GSEA) is a widely used method for interpretation of gene expression data in terms of biological processes. Here we present FGSEA method that is able to estimate arbitrarily low GSEA P-values with a higher accuracy and much faster compared to other implementations. We also present a polynomial algorithm to calculate GSEA P-values exactly, which we use to practically confirm the accuracy of the method.

Jonathon Shlens

Principal component analysis (PCA) is a mainstay of modern data analysis - a black box that is widely used but (sometimes) poorly understood. The goal of this paper is to dispel the magic behind this black box. This manuscript focuses on building a solid intuition for how and why principal component analysis works. This manuscript crystallizes this knowledge by deriving from simple intuitions, the mathematics behind PCA. This tutorial does not shy away from explaining the ideas informally, nor does it shy away from the mathematics. The hope is that by addressing both aspects, readers of all levels will be able to gain a better understanding of PCA as well as the when, the how and the why of applying this technique.

M. Spackman, D. Jayatilaka

R. Caves

T. Kanungo, D. Mount, N. Netanyahu et al.

H. Storch, F. Zwiers

H. E. Kissinger

D. Hensher, J. Rose, W. Greene

W. Güth, R. Schmittberger, Bernd Schwarze

A. Bandura

Taro Yamane

John A. Martilla, J. James

G. Jenkins, D. Watts

K. Faegri, J. Iversen

K. Helrich

R. Peterson

J. Miller

P. Slovic, Melissa L. Finucane, E. Peters et al.

J. Fodor, Z. Pylyshyn