scholarly journals A high-dimensional two-sample test for the mean using random subspaces

2014 ◽  
Vol 74 ◽  
pp. 26-38 ◽  
Author(s):  
Måns Thulin
Keyword(s):  
High Dimensional ◽  
Sample Test ◽  
The Mean ◽  
Random Subspaces

scholarly journals Mean Empirical Likelihood Inference for Response Mean with Data Missing at Random

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Hanji He ◽  
Guangming Deng
Keyword(s):  
Empirical Likelihood ◽  
Missing At Random ◽  
Confidence Regions ◽  
Likelihood Inference ◽  
High Dimensional ◽  
Finite Sample ◽  
The Mean ◽  
Data Missing ◽  
Consistency And Asymptotic Normality ◽  
The Impact

We extend the mean empirical likelihood inference for response mean with data missing at random. The empirical likelihood ratio confidence regions are poor when the response is missing at random, especially when the covariate is high-dimensional and the sample size is small. Hence, we develop three bias-corrected mean empirical likelihood approaches to obtain efficient inference for response mean. As to three bias-corrected estimating equations, we get a new set by producing a pairwise-mean dataset. The method can increase the size of the sample for estimation and reduce the impact of the dimensional curse. Consistency and asymptotic normality of the maximum mean empirical likelihood estimators are established. The finite sample performance of the proposed estimators is presented through simulation, and an application to the Boston Housing dataset is shown.

Psychometric Properties of the Children's Depression Inventory in Community and Clinical Sample

2010 ◽  
Vol 13 (2) ◽  
pp. 990-999 ◽  
Author(s):  
Anna Figueras Masip ◽  
Juan Antonio Amador-Campos ◽  
Juana Gómez-Benito ◽  
Victoria del Barrio Gándara
Keyword(s):  
Predictive Value ◽  
Clinical Sample ◽  
Community Sample ◽  
Psychometric Characteristics ◽  
Children's Depression Inventory ◽  
Children’S Depression Inventory ◽  
Children’S Depression ◽  
Sample Test ◽  
The Mean ◽  
Test Retest Reliability

The psychometric characteristics of the Children's Depression Inventory, CDI (Kovacs, 1992) in a sample of 1705 participants (792 boys and 913 girls) and a clinical sample of 102 participants (42 boys and 60 girls) between 10 and 18 years old are presented. Reliability coefficients range, for both samples, from .82 (test) to .84 (retest) in the community sample, and .85 (test, clinical sample); test-retest reliability is .81 in the community sample. The mean scores are similar to other Spanish and English ones. Girls score higher than boys. The cut-off point that best differentiates between depressive and community participants is 19, with a sensitivity of 94.7%, a specificity of 95.6%, a positive predictive value of .90, and a negative predictive value of .98.

A note on high-dimensional two-sample test

2015 ◽  
Vol 105 ◽  
pp. 29-36 ◽  
Author(s):  
Long Feng ◽  
Fasheng Sun
Keyword(s):  
High Dimensional ◽  
Sample Test

High dimensional two-sample test based on the inter-point distance

2017 ◽  
Vol 34 (2) ◽  
pp. 599-615 ◽  
Author(s):  
Shin-ichi Tsukada
Keyword(s):  
High Dimensional ◽  
Sample Test ◽  
Point Distance

High-dimensional Two-sample Test Procedures under the Strongly Spiked Eigenvalue Model

2020 ◽  
Vol 49 (3) ◽  
pp. 109-125
Author(s):  
Aki Ishii ◽  
Kazuyoshi Yata ◽  
Makoto Aoshima
Keyword(s):  
High Dimensional ◽  
Test Procedures ◽  
Sample Test
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