Pages that link to "Item:Q1941462"
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The following pages link to Asymptotic expansion and estimation of EPMC for linear classification rules in high dimension (Q1941462):
Displaying 12 items.
- A variable selection criterion for linear discriminant rule and its optimality in high dimensional and large sample data (Q391949) (← links)
- A modified linear discriminant analysis for high-dimensional data (Q455024) (← links)
- Asymptotic properties of the EPMC for modified linear discriminant analysis when sample size and dimension are both large (Q974518) (← links)
- Asymptotic cut-off point in linear discriminant rule to adjust the misclassification probability for large dimensions (Q1695766) (← links)
- Accuracy of regularized D-rule for binary classification (Q1747093) (← links)
- High-dimensional asymptotics of prediction: ridge regression and classification (Q1747738) (← links)
- EPMC estimation in discriminant analysis when the dimension and sample sizes are large (Q2357389) (← links)
- Estimation of covariance and precision matrices under scale-invariant quadratic loss in high dimension (Q2441050) (← links)
- Approximate interval estimation for EPMC for improved linear discriminant rule under high dimensional frame work (Q2831659) (← links)
- The Asymptotic Approximation of EPMC for Linear Discriminant Rules Using a Moore-Penrose Inverse Matrix in High Dimension (Q2862312) (← links)
- Distribution of the product of a Wishart matrix and a normal vector (Q6040492) (← links)
- Approximation of misclassification probabilities in linear discriminant analysis based on repeated measurements (Q6067497) (← links)
