Fetching the paper…
Reading the bibliography…
PCA is often used to visualize data when the rows and the columns are both of interest.
Schoenemann P (1966) A generalized solution of the orthogonal procrustes problem. Psychometrika 31(1):1–10
1966
Earlier work this paper cites.
Craven P, Wahba G (1979) Smoothing noisy data with spline functions. Numer Math 31(4):377–403
1979
Earlier work this paper cites.
Gabriel KR, Zamir S (1979) Lower rank approximation of matrices by least squares with any choice of weights. Technometrics 21(4):236–246
1979
Earlier work this paper cites.
Bates D, Watt D (1980) Relative curvature measure of nonlinearity. Journal of the Royal Society series B 42:1–25
1980
Earlier work this paper cites.
Efron B, Stein C (1981) The jackknife estimate of variance. Annals of Statistics 3:586–596
1981
Earlier work this paper cites.
Greenacre M (1984) Theory and Applications of Correspondence Analysis. Acadamic Press
1984
Earlier work this paper cites.
Caussinus H (1986) Models and uses of principal component analysis (with discussion). In: de Leeuw J, Heiser W, Meulman J, Critchley F (eds) Multidimensional Data Analysis, DSWO Press, pp 149–178
1986
Earlier work this paper cites.
Simonoff J, Tsai CL (1986) Jackknife-based estimators and confidence regions in nonlinear regression. Technometrics 28 (2):103–112
1986
Earlier work this paper cites.
Bartholomew DJ (1987) Latent Variable Models and Factor Analysis. Griffin
1987
Earlier work this paper cites.
Daudin JJ, Duby C, Trecourt P (1988) Stability of principal component analysis studied by the bootstrap method. Statistics: A journal of theoretical and applied statistics 19(2):241–258
1988
Earlier work this paper cites.
Gauch H (1988) Model selection and validation for yield trials with interaction. Biometrics 44:705–715
1988
Earlier work this paper cites.
Daudin JJ, Duby C, Trecourt P (1989) Pca stability studied by the bootstrap and the infinitesimal jackknife method. Statistics: A journal of theoretical and applied statistics 20(2):255–270
1989
Earlier work this paper cites.
Holmes S (1989) Using the bootstrap and the rv coefficient in the multivariate context. In: Proceedings of the conference on Data analysis, learning symbolic and numeric knowledge, vol 24, pp 119–131
1989
Earlier work this paper cites.
Besse P, de Falguerolles A (1993) Application of resampling methods to the choice of dimension in principal component analysis. In: Computer Intensive Methods in Statistics, Physica-Verlag, pp 167–176
1993
Earlier work this paper cites.
Laurent R, Cool R (1993) Leverage, local influence and curvature in nonlinear regression. Biometrika 80 (1):99–106
1993
Earlier work this paper cites.
Denis JB, Gower JC (1994) Asymptotic covariances for the parameters of biadditive models. Utilitas Mathematica pp 193–205
1994
Earlier work this paper cites.
Efron B, Tibshirani R (1994) An Introduction to the Bootstrap. Chapman & Hall/CRC
1994
Earlier work this paper cites.
Milan M (1995) Application of the parametric bootstrap to models that incorporate a singular value decomposition. Journal of the Royal Statistical Society Series C 44:31–49
1995
Earlier work this paper cites.
Chateau F, Lebart L (1996) Assessing sample variability in the visualization techniques related to principal component analysis: bootstrap and alternative simulation methods. In: Prats A (ed) COMPSTAT, Physica-Verlag, pp 205–210
1996
Cited alongside, same era.
Cornelius P, Crossa J, Seyedsadr M (1996) Statistical tests and estimators of multiplicative models for genotype by environment interaction. In: Genotype by environment interaction, M.S Kang and H.G Gauch (eds), CRC press, Boca Raton, FL, pp 199–234
1996
Cited alongside, same era.
Denis JB, Gower JC (1996) Asymptotic confidence regions for biadditive models: interpreting genotype-environment interactions. Applied Statistics 45(4):479–493
1996
Cited alongside, same era.
Gauch H, Zobel R (1996) Ammi analysis of yield trials. In: Genotype by environment interaction, M.S Kang and H.G Gauch (eds), CRC press, Boca Raton, FL, pp 141–150
1996
Cited alongside, same era.
Hoff PD (2009) Simulation of the matrix Bingham–von Mises–Fisher distribution, with applications to multivariate and relational data. Journal of Computational and Graphical Statistics 18(2):438–456
2009
Later among the works it cites.
Krzanowski WJ (2010) Principles of multivariate analysis; a user’s perspective. Clarendon Press, Oxford
2010
Later among the works it cites.
Mazumder R, Hastie T, Tibshirani R (2010) Spectral regularization algorithms for learning large incomplete matrices. Journal of Machine Learning Research 99:2287–2322
2010
Later among the works it cites.
Josse J, Husson F (2011) Selecting the number of components in pca using cross-validation approximations. Computational Statististics and Data Analysis 56(6):1869–1879
2011
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Kiers HAL (1997) Weighted least squares fitting using ordinary least squares algorithms. Psychometrika 62(2):251–266
1997
Cited alongside, same era.
Denis JB, Pazman A (1999) Bias of least squares estimators in nonlinear regression models with constraints. part ii: Biadditive models. Applications of Mathematics 44:359–374
1999
Cited alongside, same era.
Huet S, Denis JB, Adamczyk K (1999) Bootstrap confidence intervals in nonlinear regression models when the number of observations is fixed and the variance tends to 0. application to biadditive model. Statistics 32:203–227
1999
Cited alongside, same era.
Tipping M, Bishop CM (1999) Probabilistic principal component analysis. Journal of the Royal Statistical Society B 61(3):611–622
1999
Cited alongside, same era.
Papadopoulo T, Lourakis MIA (2000) Estimating the jacobian of the singular value decomposition: Theory and applications. In: In Proceedings of the European Conference on Computer Vision, ECCV00, Springer, pp 554–570
2000
Cited alongside, same era.
Jolliffe IT (2002) Principal Component Analysis. Springer
2002
Cited alongside, same era.
Pazman A (2002) Results on nonlinear least squares estimators under nonlinear equality constraints. Journal of statistical planning and inference 103:401–420
2002
Cited alongside, same era.
Pazman A, Denis JB (2002) Measures of nonlinearity for biadditive anova models. Metrika 55 (3):233–245
2002
Cited alongside, same era.
2011
Later among the works it cites.
Josse J, Husson F (2012) Handling missing values in exploratory multivariate data analysis methods. Journal de la Société Française de Statistique 153(2):79–99
2012
Later among the works it cites.
Badamoradi H, van den Berg F, Rinnan A (2013) Bootstrap based confidence limits in principal component analysis - a case study. Chemometrics and Intellligent Laboratory Systems 120:97–105
2013
Later among the works it cites.
Chatterjee S (2013) Matrix estimation by universal singular value thresholding. arXiv:12121247
2013
Later among the works it cites.
Donoho DL, Gavish M (2013) The optimal hard threshold for singular values is 4/sqrt(3). arXiv:13055870
2013
Later among the works it cites.
Efron B (2013) Estimation and accuracy after model selection. Journal of the American Statistical Association (just-accepted)
2013
Later among the works it cites.
Rao NR (2013) Optshrink - low-rank signal matrix denoising via optimal, data- driven singular value shrinkage. arXiv:13066042
2013
Later among the works it cites.
Shabalin AA, Nobel B (2013) Reconstruction of a low-rank matrix in the presence of Gaussian noise. Journal of Multivariate Analysis 118(0):67 – 76
2013
Later among the works it cites.
Verbanck M, Husson F, Josse J (2013) Regularized PCA to denoise and visualize data. Statistics and Computing forthcoming
2013
Later among the works it cites.
2013
Later among the works it cites.
Josse J, Sardy S (2014) Selecting thresholding and shrinking parameters with generalized SURE for low rank matrix estimation. arXiv 13106602
2014
Closest in time.
Josse J, van Eeuwijk F, Piepho HP, Denis JB (2014) Another look at bayesian analysis of ammi models for genotype-environment data. Journal of Agricultural, Biological, and Environmental Statistics pp 1–18
2014
Closest in time.
Candes E, Tao T (2009) The power of convex relaxation: Near-optimal matrix completion. IEEE Trans Inform Theory 56(5):2053–2080
2080
Closest in time.