Partial information framework: Model-based aggregation of estimates from diverse information sources
نویسندگان
چکیده
منابع مشابه
Partial Information Framework: Model-Based Aggregation of Estimates from Diverse Information Sources∗
Prediction polling is an increasingly popular form of crowdsourcing in which multiple participants estimate the probability or magnitude of some future event. These estimates are then aggregated into a single forecast. Historically, randomness in scientific estimation has been generally assumed to arise from unmeasured factors which are viewed as measurement noise. However, when combining subje...
متن کاملPartial Information Framework: Aggregating Estimates from Diverse Information Sources
Prediction polling is an increasingly popular form of crowdsourcing in which multiple participants estimate the probability or magnitude of some future event. These estimates are then aggregated into a single forecast. Historically, randomness in scientific estimation has been generally assumed to arise from unmeasured factors which are viewed as measurement noise. However, when combining subje...
متن کاملPartial information framework: Model-based aggregation of estimates from diverse information sourcesT1
Prediction polling is an increasingly popular form of crowdsourcing in which multiple participants estimate the probability or magnitude of some future event. These estimates are then aggregated into a single forecast. Historically, randomness in scientific estimation has been generally assumed to arise from unmeasured factors which are viewed as measurement noise. However, when combining subje...
متن کاملCombining Information from Diverse Sources
Research synthesis plays a central role in the process of scientific discovery, providing a formal methodology for the systematic accumulation and evaluation of scientific evidence. There are many situations in which research synthesis is required because obtaining the required information from an individual trial is not possible or practical. This thesis proposes a general method to synthesize...
متن کاملBayesian aggregation of two forecasts in the partial information framework
We generalize the results of Satopää et al. (2014, 2015) by showing how the Gaussian aggregator may be computed in a setting where parameter estimation is not required. We proceed to provide an explicit formula for a “one-shot” aggregation problem with two forecasters.
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ژورنال
عنوان ژورنال: Electronic Journal of Statistics
سال: 2017
ISSN: 1935-7524
DOI: 10.1214/17-ejs1346