Continuous Joint Distributions
Continuous Joint Distributions is a type of joint probability distribution that describes the likelihood of two or more continuous random variables simultaneously taking on specific values within a continuous domain, characterized by a probability density function that integrates to one over the entire space.
116
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7.3K
Citations
233
Authors
145
Institutions
Publications per year
2017–2026
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116
A Non-Parametric Test of Independence
Wassily Hoeffding · The Annals of Mathematical Statistics · 1948 · 643 citations · Full text
William F. Darsow, Bao Nguyen, Elwood T. Olsen · Illinois Journal of Mathematics · 1992 · 333 citations · Full text
Natural Sciences, Mathematics, Markov Decision Processes +15
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The University of Osaka
Osaka, Japan
4 h-index
6 publications
161 citations

Cornell University
Ithaca, United States
3 h-index
3 publications
381 citations
Indiana University – Purdue University Indianapolis
Indianapolis, United States
3 h-index
3 publications
124 citations
The Institute of Statistical Mathematics
Tokyo, Japan
3 h-index
3 publications
55 citations
Purdue University West Lafayette
West Lafayette, United States
2 h-index
3 publications
49 citations

City, University of London
London, United Kingdom
2 h-index
2 publications
80 citations
Procter & Gamble (United States)
Cincinnati, United States
2 h-index
2 publications
169 citations

The Graduate Center, CUNY
New York, United States
2 h-index
2 publications
171 citations
1–8 of 145
6 publications · 129 citations
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5 publications · 1.1K citations
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4 publications · 383 citations
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4 publications · 543 citations
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JAP · 4 publications · 334 citations
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