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ESAIM: PROCEEDINGS AND SURVEYS, September 2023, Vol. 73, p. 238256 Virginie Ehrlacher, Damiano Lombardi, Olga Mula, Fabio Nobile, Tommaso TaddeiGENERATIVE METHODS FOR SAMPLING TRANSITION PATHS IN
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Identify the target distribution you want to sample from.
02
Choose a generative model that is capable of representing your target distribution.
03
Specify the parameters of the generative model based on your understanding of the data.
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Generative methods for sampling refer to statistical techniques used to generate samples from a population or a model. These methods create new data points based on existing data distributions.
Organizations and researchers conducting studies that involve sampling methods, particularly when they need to ensure compliance with statistical standards or regulatory requirements, are typically required to file generative methods for sampling.
To fill out generative methods for sampling, individuals must provide detailed descriptions of the sampling process, including the population being studied, the sampling technique used, and the methodology for data generation. Templates or forms provided by regulatory bodies may also need to be followed.
The purpose of generative methods for sampling is to allow researchers to create representative samples that can be used for analysis, hypothesis testing, and decision-making, while also ensuring the validity and reliability of statistical results.
Information that must be reported includes the objectives of the sampling, description of the population, sampling technique employed, the size of the sample, and any assumptions made during the sampling process.
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