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| 1 |
A study on the difference and calibration of empirical influence function and sample influence function
Kang, Hyunseok;Kim, Honggie;
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The Korean Statistical Society
, v.33, no.5, pp.527-540,
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| 2 |
Partial AUC using the sensitivity and specificity lines
Hong, Chong Sun;Jang, Dong Hwan;
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The Korean Statistical Society
, v.33, no.5, pp.541-553,
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| 3 |
Comparison of nomograms designed to predict hypertension with a complex sample
Kim, Min Ho;Shin, Min Seok;Lee, Jea Young;
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The Korean Statistical Society
, v.33, no.5, pp.555-567,
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| 4 |
Divide and conquer kernel quantile regression for massive dataset
Bang, Sungwan;Kim, Jaeoh;
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The Korean Statistical Society
, v.33, no.5, pp.569-578,
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| 5 |
The number of games of Rock-Paper Scissors according to game rules
Cho, Daehyeon;
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The Korean Statistical Society
, v.33, no.5, pp.579-590,
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| 6 |
A new cluster validity index based on connectivity in self-organizing map
Kim, Sangmin;Kim, Jaejik;
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The Korean Statistical Society
, v.33, no.5, pp.591-601,
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| 7 |
Prediction and factors of Seoul apartment price using convolutional neural networks
Lee, Hyunjae;Son, Donghui;Kim, Sujin;Oh, Sein;Kim, Jaejik;
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The Korean Statistical Society
, v.33, no.5, pp.603-614,
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| 8 |
Document classification using a deep neural network in text mining
Lee, Bo-Hui;Lee, Su-Jin;Choi, Yong-Seok;
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The Korean Statistical Society
, v.33, no.5, pp.615-625,
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| 9 |
Predicting the number of disease occurrence using recurrent neural network
Lee, Seunghyeon;Yeo, In-Kwon;
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The Korean Statistical Society
, v.33, no.5, pp.627-637,
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| 10 |
New economic policy uncertainty indexes for South Korea
Lee, Geung-Hee;Cho, Joo-Hee;Jo, Jin-Gyeong;
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The Korean Statistical Society
, v.33, no.5, pp.639-653,
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| 11 |
A GSADF bubble test analysis for COVID-19 pandemic
Shin, Jiwon;Shin, Dong Wan;
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The Korean Statistical Society
, v.33, no.5, pp.655-664,
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