Journal of Multivariate Analysis
ISSN: 0047-259X
Datasets associated with articles published in Journal of Multivariate Analysis
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- Data for: Two-way MANOVA with unequal cell sizes and unequal cell covariance matrices in high-dimensional settingsMathematica code for the proposed tests
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- Data for: Conditional probability estimation based classification with class label missing at randomhe breast cancer dataset studied by \citet{Cummings1986Tamoxifen}, which is conducted to evaluate tamoxifen as a treatment for stage \uppercase\expandafter{\romannumeral2} breast cancer among elder women. In this dataset, 78 patients died during the clinical trial. Specifically, 43 of them died from breast cancer, 17 of them died from other known reasons and the remaining 18 patients died from unknown reasons. Therefore, we have two types of cause of death: breast cancer (class 1) and other known reasons (class 0). Moreover, 43 samples come from class 1, 17 samples come from class 0 and class labels of 18 samples are missing. According to \citet{chen2018reweighted}, we choose the observed survival time of a patient as the predictor and assume that the class label is missing at random (MAR).
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- Data for: Quasi-Bayesian estimation of large Gaussian graphical modelsData and Matlab code to reproduce the real data example in the paper.
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- Data for: Fixed support positive-definite modification of covariance matrix estimators via linear shrinkageFixed support positive definite modification of covariance matrix estimators via linear shrinkage by Young-Geun Choi, Junyong Park, Anindya Roy, and Johan Lim Chapter 4. Simulations run the followings consequtively (1 -> 2 -> 3 and 4): 1. (repeatedly generate data and calculate estimators and store results) /simulation/simul_cov/covsim.R 2. (aggregate results over replications) /simulation/simul_cov/replication_aggregate.R 3. (2.1 empirical spectrum) /simulation/simul_cov/result_empiricalspectrum.R 4. (2.2 error comparison) /simulation/simul_cov/result_empiricalerrors.R Chapter 5. Data examples 5.1. Speech recognition (coded in MATLAB): run /data_examples/1_speech/DA_main.m 5.2. Portfolio (coded in MATLAB): run /data_examples/2_portfolio/positiveMVR_exec_daily.m and simpleMVR_exec_daily.m
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- Data for: Efficient Predictor Ranking and False Discovery Proportion Control in High-Dimensional RegressionThis file provides the algorithm of the proposed DLasso-FDP method in R.
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- Data for: A novel mixture model using multivariate normal mean-variance mixture of Birnbaum-Saunders distribution and its application to extrasolar planetsThe data are from the Extrasolar Planets Encyclopaedia (http://exoplanet.eu/). We use the data of April 2017 and exclude the incomplete ones. There are 965 planets available in this study.
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- Data for: Substationarity for Spatial Point ProcessesData and R Codes
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- Data for: General Gaussian EstimationThis is a classical data set for epileptic patients which has been used by many authors. We used longitudinal data approach in the analysis.
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- Data for: An RKHS model for variable selection in functional linear regressionR code used in "An RKHS model for variable selection in functional linear regression".
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- Data for: Small area estimation with multiple covariates measured with errors: A nested error linear regression approach of combining multiple surveysThe R codes, corresponding read me files, and related datasets for the simulation and application conducted in this paper are provided.
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