Pages that link to "Item:Q1761307"
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The following pages link to Multiple imputation in principal component analysis (Q1761307):
Displaying 15 items.
- Imputation Scores (Q116910) (← links)
- Using generalized Procrustes analysis for multiple imputation in principal component analysis (Q288990) (← links)
- Another look at Bayesian analysis of AMMI models for genotype-environment data (Q486188) (← links)
- An imputation method for categorical variables with application to nonlinear principal component analysis (Q901642) (← links)
- Principal component analysis with interval imputed missing values (Q1633223) (← links)
- Prediction regions for the visualization of incomplete data sets (Q1861586) (← links)
- Comparisons among several methods for handling missing data in principal component analysis (PCA) (Q1999456) (← links)
- Gaussian-based visualization of Gaussian and non-Gaussian-based clustering (Q2040030) (← links)
- Chunk-wise regularised PCA-based imputation of missing data (Q2152199) (← links)
- A principal component method to impute missing values for mixed data (Q2418252) (← links)
- A sequential distance-based approach for imputing missing data: forward imputation (Q2418314) (← links)
- Constructing bootstrap confidence intervals for principal component loadings in the presence of missing data: A multiple‐imputation approach (Q4561348) (← links)
- Relationships Between two Methods for Dealing with Missing Data in Principal Component Analysis (Q4652178) (← links)
- A simulation comparison of imputation methods for quantitative data in the presence of multiple data patterns (Q4960780) (← links)
- Online Principal Component Analysis in High Dimension: Which Algorithm to Choose? (Q6086546) (← links)
