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Optimal design via curve fitting of Monte Carlo experiments
Peter Müller, Giovanni Parmigiani
Research output
:
Contribution to journal
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Article
›
peer-review
97
Scopus citations
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Dive into the research topics of 'Optimal design via curve fitting of Monte Carlo experiments'. Together they form a unique fingerprint.
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Mathematics
Expected Utility
80%
Curve fitting
73%
Monte Carlo Experiment
70%
Bayesian Design
57%
Stochastic Optimization
46%
Optimization Algorithm
42%
Design
37%
Objective function
33%
Implantation
32%
Stochastic Dynamic Programming
31%
Optimization
30%
Sequential Design
27%
Alternatives
24%
Sample space
24%
Stopping Rule
23%
Smooth surface
23%
Heart
21%
Dimensionality
20%
Shock
19%
Clinical Trials
18%
Parameter Space
18%
Efficient Algorithms
17%
Smoothness
16%
Evaluate
15%
Numerical Methods
14%
Estimate
9%
Class
5%
Business & Economics
Curve Fitting
100%
Monte Carlo Experiment
68%
Expected Utility
48%
Stochastic Optimization
30%
Objective Function
22%
Stopping Rule
16%
Implantation
16%
Stochastic Dynamic Programming
15%
Numerical Methods
14%
Clinical Trials
14%
Dimensionality
13%
Efficiency Gains
12%
Borrowing
11%
Alternatives
11%
Attraction
11%