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Parametric likelihood inference for record breaking problems
Bradley P. Carlin, Alan E. Gelfand
Biostatistics
Research output
:
Contribution to journal
›
Article
›
peer-review
16
Scopus citations
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Dive into the research topics of 'Parametric likelihood inference for record breaking problems'. Together they form a unique fingerprint.
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Mathematics
Parametric Inference
94%
Likelihood Inference
80%
Likelihood Function
43%
Observation
42%
Multivariate integral
34%
Mean Shift
29%
Monte Carlo Integration
28%
Mining
27%
Rendering
26%
Gibbs Sampler
25%
Threshold Value
25%
Maximum Likelihood Method
23%
Parametric Model
22%
Missing Data
22%
Data Structures
22%
Model Selection
21%
Exceed
19%
Jump
17%
High-dimensional
17%
Prediction
17%
Evaluate
17%
Methodology
15%
Testing
15%
Dependent
14%
Modeling
14%
Context
13%
Approximation
10%
Business & Economics
Inference
53%
Integral
36%
Monte Carlo Integration
34%
Mean Shift
33%
Model Selection
32%
Gibbs Sampler
32%
Stress Testing
28%
Missing Data
28%
Data Structures
27%
Athletics
27%
Parametric Model
26%
Extreme Values
26%
Jump
25%
Maximum Likelihood
21%
Approximation
17%
Prediction
17%
Oil
15%
Modeling
12%
Methodology
10%
Medicine & Life Sciences
Likelihood Functions
100%
Monte Carlo Method
47%
Oils
32%
Sports
28%
Datasets
25%
Agriculture & Biology
samplers
25%
rendering
24%
sports
23%
methodology
17%
prediction
14%
oils
13%
testing
8%
Engineering & Materials Science
Maximum likelihood
30%
Data structures
26%
Oils
20%
Testing
16%