query: PCA: violation of the normal distribution assumption
positive_passages.docid: 156166
positive_passages.text: PCA of non-Gaussian data
negative_passages.docid: 126726
negative_passages.text: PCA, LDA, CCA, and PLS
negative_passages.docid: 67557
negative_passages.text: Imputation of missing values for PCA
negative_passages.docid: 3089
negative_passages.text: Why PCA of data by means of SVD of the data?
negative_passages.docid: 154899
negative_passages.text: Is it valid to perform PCA if Kaiser-Meyer-Olkin (KMO) index is very low?
negative_passages.docid: 111170
negative_passages.text: Testing large dataset for normality - how and is it reliable?
negative_passages.docid: 34399
negative_passages.text: Nonstandard normal distribution
negative_passages.docid: 119647
negative_passages.text: Average norm of a N-dimensional vector given by a normal distribution
negative_passages.docid: 36477
negative_passages.text: Is there any required amount of variance captured by PCA in order to do later analyses?
negative_passages.docid: 51254
negative_passages.text: How to project a new vector onto the PC space using kernel PCA?
negative_passages.docid: 46319
negative_passages.text: How to perform orthogonal regression (total least squares) via PCA?
negative_passages.docid: 116362
negative_passages.text: Is PCA unstable under multicollinearity?
negative_passages.docid: 84446
negative_passages.text: How to project a new vector onto PCA space?
negative_passages.docid: 14181
negative_passages.text: Can averaging all the variables be seen as a crude form of PCA?
negative_passages.docid: 112134
negative_passages.text: What are principal component scores?
negative_passages.docid: 141614
negative_passages.text: Linear Combination of Random Normal Variables
negative_passages.docid: 25410
negative_passages.text: What is an intuitive explanation for how PCA turns from a geometric problem (with distances) to a linear algebra problem (with eigenvectors)?